CN112309539A - Intelligent correction method and device for liquid output parameters of injection system - Google Patents
Intelligent correction method and device for liquid output parameters of injection system Download PDFInfo
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Abstract
The invention relates to an intelligent correction method and equipment for liquid output parameters of an injection system, and belongs to the technical field of equipment control. The method comprises the following steps: reading an index value corresponding to at least one parameter influence index from a data storage space; inputting the index value into a pre-constructed correction coefficient determination model so that the correction coefficient determination model outputs a corresponding correction coefficient according to the input index value; acquiring basic output parameters of liquid to be output; determining a correction coefficient output by the model according to the correction coefficient, and performing at least one-stage correction on the basic output parameter to obtain a corrected output parameter; the corrected output parameters are used for controlling the output state of the liquid output equipment to the liquid to be output. According to the technical scheme, the automatic correction process of the liquid output parameters can be automatically completed by computer equipment, and the control efficiency of liquid output can be effectively improved.
Description
Technical Field
The invention relates to the technical field of equipment control, in particular to an intelligent correction method, an intelligent correction device, computer equipment and a computer readable storage medium for liquid output parameters of an injection system, and the injection system.
Background
In many scenarios, it is desirable to control the output of a liquid, for example, in a laboratory, hospital, etc. The traditional way of controlling the liquid output is to manually infuse the liquid into a certain subject in a fixed dose, which is greatly influenced by human factors, resulting in a great difference in output effect among different subjects. With the development of science and technology, a mode of controlling liquid output through liquid output equipment according to certain output parameters exists at present.
In the process of implementing the invention, the inventor finds that the prior art has the following problems: the current liquid output equipment is used for outputting liquid according to output parameters determined by a single factor. In fact, the liquid output process is influenced by many factors, and the efficiency of liquid output is not high only by controlling the output parameters according to a single factor, so that the effect of the liquid output to a specific object is not ideal.
Disclosure of Invention
Based on the above, the invention provides an intelligent correction method, an intelligent correction device, a computer device and a computer readable storage medium for liquid output parameters of an injection system, and the injection system, which can effectively improve the liquid output efficiency.
The content of the embodiment of the invention is as follows:
an intelligent correction method applied to a liquid output parameter of an injection system is applied to computer equipment and comprises the following steps: reading an index value corresponding to at least one parameter influence index from a data storage space; the parameter influence index is an index which influences the blood concentration of the target object; wherein the target object is an organism for absorbing the liquid to be output; inputting the index value into a pre-constructed correction coefficient determination model so that the correction coefficient determination model outputs a corresponding correction coefficient according to the input index value; acquiring basic output parameters of liquid to be output; determining a correction coefficient output by the model according to the correction coefficient, and performing at least one-stage correction on the basic output parameter to obtain a corrected output parameter; and the corrected output parameters are used for controlling the output state of the liquid output equipment to the liquid to be output.
An intelligent correction device applied to a liquid output parameter of an injection system, applied to a computer device, comprises: the index value acquisition module is used for reading an index value corresponding to at least one parameter influence index from the data storage space; the parameter influence index is an index which influences the blood concentration of the target object; wherein the target object is an organism for absorbing the liquid to be output; the model input module is used for inputting the index value into a pre-constructed correction coefficient determination model so that the correction coefficient determination model outputs a corresponding correction coefficient according to the input index value; the basic parameter acquisition module is used for acquiring basic output parameters of the liquid to be output; the parameter correction module is used for determining a correction coefficient output by the model according to the correction coefficient and performing at least one-stage correction on the basic output parameter to obtain a corrected output parameter; and the corrected output parameters are used for controlling the output state of the liquid output equipment to the liquid to be output.
A computer device comprising a memory and a processor, the memory storing a computer program, the processor implementing the following steps when executing the computer program: reading an index value corresponding to at least one parameter influence index from a data storage space; the parameter influence index is an index which influences the blood concentration of the target object; wherein the target object is an organism for absorbing the liquid to be output; inputting the index value into a pre-constructed correction coefficient determination model so that the correction coefficient determination model outputs a corresponding correction coefficient according to the input index value; acquiring basic output parameters of liquid to be output; determining a correction coefficient output by the model according to the correction coefficient, and performing at least one-stage correction on the basic output parameter to obtain a corrected output parameter; and the corrected output parameters are used for controlling the output state of the liquid output equipment to the liquid to be output.
A computer-readable storage medium, on which a computer program is stored which, when executed by a processor, carries out the steps of: reading an index value corresponding to at least one parameter influence index from a data storage space; the parameter influence index is an index which influences the blood concentration of the target object; wherein the target object is an organism for absorbing the liquid to be output; inputting the index value into a pre-constructed correction coefficient determination model so that the correction coefficient determination model outputs a corresponding correction coefficient according to the input index value; acquiring basic output parameters of liquid to be output; determining a correction coefficient output by the model according to the correction coefficient, and performing at least one-stage correction on the basic output parameter to obtain a corrected output parameter; and the corrected output parameters are used for controlling the output state of the liquid output equipment to the liquid to be output.
According to the intelligent correction method, the intelligent correction device, the computer equipment and the computer readable storage medium for the liquid output parameter applied to the injection system, the correction coefficient is determined based on the index value corresponding to the parameter influence index, and the basic output parameter is corrected based on the correction coefficient to obtain the corrected output parameter which can be used for controlling the output state of the liquid output equipment to be output. The automatic correction process of the liquid output parameters can be automatically completed by computer equipment, so that the automatic control of the liquid output state to be output by the liquid output equipment is realized, manual parameters are not needed, and the control efficiency of liquid output can be effectively improved.
An injection system comprising a controller and an injector; the injector is used for containing liquid to be output; the controller is connected with the injector network; the controller is configured to: reading an index value corresponding to at least one parameter influence index from a data storage space; the parameter influence index is an index which influences the blood concentration of the target object; wherein the target object is an organism for absorbing the liquid to be output; inputting the index value into a pre-constructed correction coefficient determination model so that the correction coefficient determination model outputs a corresponding correction coefficient according to the input index value; acquiring basic output parameters of liquid to be output; determining a correction coefficient output by the model according to the correction coefficient, and performing at least one-stage correction on the basic output parameter to obtain a corrected output parameter; sending a medicine output instruction to a signal input interface of the injector according to the corrected output parameters; the syringe is used for: and injecting the liquid to be output to the target object according to the corrected output parameters under the triggering of the medicine output instruction.
In the injection system, the controller determines a correction coefficient based on an index value corresponding to the parameter influence index, corrects the basic output parameter based on the correction coefficient to obtain a corrected output parameter which can be used for controlling the output state of the liquid output equipment to the liquid to be output, and the injector injects the liquid to be output to the target object based on the corrected output parameter. The corrected injection parameters obtained through multi-stage correction have a good fluid concentration control effect, automatic control over the injector is achieved under the condition that the injection effect of the injector is guaranteed, manual participation is not needed, and the injection efficiency of liquid is effectively improved.
Drawings
FIG. 1 is a diagram of an embodiment of a method for intelligently modifying fluid output parameters of an injection system;
FIG. 2 is a schematic flow diagram of a method for intelligent correction of fluid output parameters for an injection system in one embodiment;
FIG. 3 is a schematic flow chart illustrating a method for intelligently modifying a fluid output parameter of an infusion system in accordance with another embodiment;
FIG. 4 is a block diagram of an embodiment of an intelligent correction device for fluid output parameters applied to an infusion system;
FIG. 5 is an internal structure of a computer apparatus in one embodiment;
fig. 6 shows the internal structure of the injection system in one embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.
Embodiments of the present invention provide an intelligent correction method, apparatus, computer device and computer-readable storage medium for a liquid output parameter applied to an injection system, and the injection system, which are described in detail below.
The intelligent correction method applied to the liquid output parameter of the injection system can be applied to the application environment shown in fig. 1. The application environment includes a computer device 101 and an injector 102, both of which communicate over a network. The computer apparatus 101 obtains a correction coefficient according to the parameter influence index, corrects the basic output parameter according to the correction coefficient to obtain a corrected output parameter, and controls the output state of the syringe for the liquid to be output based on the corrected output parameter. The computer device 101 may be a terminal or a server, where the terminal may be, but is not limited to, various personal computers, notebook computers, smart phones, tablet computers, and portable wearable devices, and the server may be implemented by an independent server or a server cluster composed of multiple servers.
In some embodiments, the computer device itself may also be a syringe that includes a controller, i.e., capable of containing the liquid to be delivered, the controller automatically modifies the base delivery parameter, and the syringe delivers the liquid to be delivered to the target object via a conduit, needle, etc., based on the modified base delivery parameter.
In one embodiment, as shown in fig. 2, an intelligent correction method applied to a liquid output parameter of an injection system is provided, and this embodiment is exemplified by applying the method to a computer device, it is to be understood that the computer device may be a terminal, a server, or a system including a terminal and a server, and is implemented by interaction between the terminal and the server. The method comprises the following steps:
s201, reading an index value corresponding to at least one parameter influence index from a data storage space; the parameter influence index is an index which influences the blood concentration of the target object; wherein the target object is an organism for absorbing the liquid to be output.
The data storage space may be a cache, a memory, or the like of the computer device. The computer device can receive the index values of the parameter influence indexes input by the user through the input device and write the index values into the data storage space. And when a correction instruction of the basic output parameter is received, the computer equipment reads an index value corresponding to the parameter influence index from the data storage space.
In one embodiment, the correction factor determination model is associated with the number and content of parameter impact indicators. The computer device may read the parameter impact indicators of the corresponding quantity and content from the data storage space according to the correction factor determination model.
The target object may refer to a specific organism capable of containing a liquid. Specifically, the target object may be a human body model, an organ model, an isolated tissue, an isolated organ, a cell, etc., or may be a specific biological, chemical, pathological test object. It should be noted that the human body model in the embodiment of the present invention may be manufactured according to the requirements of some physiological and medical experiments, and is a model capable of simulating some physiological and pathological functions of a human body. Further, the mannequin may have a particular height, weight, temperature, heart rate, body fat content, metabolic state, etc., and may have a circulatory blood system. Further, the human body model can represent the difference of human body physiological functions, such as: fat content in the obese manikin is higher than that in the normal manikin, the female manikin and the male manikin have difference in hormone content, and the old manikin has weaker organ function than the old manikin.
The liquid to be delivered may refer to various types of solutions, drugs, etc., such as: hydrochloric acid solution, normal saline, glucose solution, injection, etc.
The target object may contain a liquid, and the concentration of the original liquid in the target object may be affected when the liquid to be output is output to the target object. In the case of pathological tests, the blood concentration of a target object may refer to the plasma drug concentration in a certain isolated muscle tissue, and after injecting a drug into the isolated muscle tissue, the isolated muscle tissue reacts to the injected drug and may cause the plasma drug concentration to change.
The parameter influence index is an index for evaluating the influence of the liquid to be output on the blood concentration of the target object. The parameter influence index may include an environmental factor, a state of the liquid to be output, a state of the target object, a reaction of the target object to the liquid to be output, and the like. Wherein, the environmental factor can refer to the temperature, humidity, etc. of the surrounding environment; the state of the liquid to be output can refer to the concentration, temperature, molecular weight of the medicine and the like of the liquid to be output; the state of the target object may refer to the state of the target object, e.g., volume, temperature, weight, etc.; the reaction of the target object to the liquid to be delivered can be determined by visual observation, instrumental measurement, and the like, for example, in the case that the target object is an isolated muscle tissue, the temperature change of the muscle tissue after the injection of the liquid to be delivered can be measured by a thermometer.
In one embodiment, the effect of the parameter impact indicator on the blood concentration may be characterized by a correspondence between the parameter impact indicator and the blood concentration. The correspondence may be a number of calculation formulas; it can also be implemented by other means than calculation formula, for example: the molecular weight of a drug is large, and the blood concentration of the drug in a target object is continuously maintained at a high level, so that the correspondence relationship can be determined as the molecular weight of the drug → the blood concentration is high. In this case, the correction coefficient determination model may classify the strength of the correspondence relationship into classes, quantize the classified classes, and determine the corresponding correction coefficient based on the input index value and the quantized class.
S202, inputting the index value into a pre-constructed correction coefficient determination model, so that the correction coefficient determination model outputs a corresponding correction coefficient according to the input index value.
The correction coefficient determination model may be a correction coefficient calculation formula, or may be a neural network model or the like that can generate a correction coefficient based on an input index value.
In one embodiment, the correction coefficient determination model obtains a corresponding relationship between the index value and the correction coefficient, and determines the corresponding correction coefficient according to the input index value and the corresponding relationship.
S203, acquiring basic output parameters of the liquid to be output.
The basic output parameters of the liquid to be output can be obtained according to the weight of the target object.
In one embodiment, S203 may obtain a basic output parameter of the liquid to be output according to the liquid consumption characteristic of the target object. Wherein, the liquid consumption characteristic may refer to a consumption characteristic of the target object to the liquid to be output, such as: consumption rate, etc. In one embodiment, the liquid consumption characteristic may be determined from an object characteristic of the target object and a liquid characteristic of the liquid to be output. Wherein, the object characteristic may refer to the capacity, temperature, weight, volume, etc. of the target object, and the liquid characteristic may refer to the concentration, dosage, volume, etc. of the liquid to be output.
The basic output parameters may refer to parameters when the liquid output device outputs the liquid to be output, and may include output speed, output flow rate, output time, and the like. In one embodiment, the base output parameter may be an injection parameter, which may include injection speed, injection flow, injection time, etc.; wherein, the injection speed can be constant speed, step speed change, linear speed change and the like. The injection flow rate can refer to the aperture of the injection head, and the control of the injection flow rate can be realized by controlling the aperture of the injection head, or can be realized by selecting the injection equipment with the corresponding aperture from a plurality of injection equipment with different apertures. In some scenarios, the injection parameters may also include concentration, temperature, viscosity, etc. of the injection fluid. Specifically, in an isolated muscle tissue experiment, physiological saline is injected into the isolated muscle tissue through intravenous injection at an injection speed of 5mL/min, and the injection speed, the composition and the concentration of the physiological saline can be understood as injection parameters, namely basic injection parameters.
In one embodiment, the correspondence of the liquid consumption characteristics and the basic output parameters may be pre-constructed. And when the computer equipment acquires the liquid consumption characteristics, determining corresponding basic output parameters according to the corresponding relation.
S204, determining a correction coefficient output by the model according to the correction coefficient, and performing at least one-stage correction on the basic output parameter to obtain a corrected output parameter; and the corrected output parameters are used for controlling the output state of the liquid output equipment to the liquid to be output.
In one embodiment, the basic injection parameter may be modified by performing a certain operation on the basic output parameter and the modification coefficient, for example: multiplication, and the like. The correction factor may be one, two or even more. For the case of one correction factor, the basic injection parameter can be corrected a number of cycles by the correction factor. For the case that the correction coefficients are two or more, the correction coefficients can be used for respectively correcting the basic injection parameters, and the corrected output parameters are obtained by integrating the basic injection parameters obtained by respective correction; or the correction coefficients are used for correcting the basic injection parameters step by step to obtain corrected output parameters; or the correction coefficients can be integrated firstly, and the basic injection parameters are corrected through the integrated comprehensive correction coefficients to obtain corrected output parameters.
The liquid output device refers to a device with a liquid output function, and can be a syringe pump, a syringe and the like. Specifically, the liquid output device may be, but is not limited to, a micro syringe pump, an industrial syringe pump, a medical syringe pump, and the like. In one embodiment, the number of liquid output devices may be 1, 2, or even more, and the computer device may selectively perform output control on these liquid output devices. Furthermore, each liquid output device can act on the same target object, namely, the liquid to be output is output to the target object together; the individual liquid discharge devices can also act on different target objects, i.e. they each discharge the liquid to be discharged to the connected target object.
According to the intelligent correction method for the liquid output parameter applied to the injection system, the correction coefficient is determined based on the index value corresponding to the parameter influence index, and the basic output parameter is corrected based on the correction coefficient, so that the corrected output parameter which can be used for controlling the output state of the liquid output equipment to be output is obtained. The automatic correction process of the liquid output parameters can be automatically completed by the computer equipment, so that the automatic control of the liquid output state to be output by the liquid output equipment is realized, manual parameters are not needed, and the influence of human factors is avoided, so that the control efficiency of liquid output can be effectively improved. Meanwhile, output control can be performed on a plurality of liquid output devices at the same time, and the control efficiency of liquid output can be further improved.
In one embodiment, the liquid to be delivered is a drug to be delivered; the step of reading an index value corresponding to at least one parameter influence index from the data storage space includes: determining a parameter influence index; the parameter impact indicator comprises at least one of: physiological index, pathological signs, clinical response characteristics of the target subject, and pharmacological characteristics of the fluid to be output; and reading an index value corresponding to at least one parameter influence index from a data storage space.
The physiological index may refer to a characteristic index of a target subject on physiology and body, and may include sex, age/week, height, weight, waist circumference, heart rate, body fat content, metabolic state, temperature, and the like. The pathological characteristics can refer to the diseased state of the target object and the reaction after the liquid to be output is injected, and can comprise disease signs, target organ signs, drug metabolism characteristics of the target object and the like; further, the drug metabolism characteristics of the target object may be further subdivided, for example: critical patients' pharmacokinetic properties, neonatal pharmacokinetic properties, multi-condition combined drug metabolic properties, etc. The clinical response characteristic, i.e. the post-injection state, may refer to the response of the target object to the injection of the liquid to be delivered, for example: changes in body temperature, changes in organ status, etc. The pharmacological property of the liquid to be delivered may refer to a change in the drug after entering the target subject, and may include: onset time, half-life, ph, molecular weight, lipophilicity, hydrophilicity, elimination rate constant, drug accumulation ratio, therapeutic index, maintenance dose, metabolic organ, safety threshold, plasma protein binding rate, and the like.
The embodiment reads the index value corresponding to the parameter influence index from the data storage space, can realize automatic correction of the basic output parameter based on the pre-recorded index value, and effectively improves the automatic correction efficiency of the liquid output parameter.
In one embodiment, the modification coefficients corresponding to different parameter influence indicators may be different, and may include: a physiological correction coefficient corresponding to the physiological index, a pathological correction coefficient corresponding to the pathological feature, a pharmacological correction coefficient corresponding to the pharmacological property, and a state correction coefficient corresponding to the post-injection state.
Further, the computer device may determine the correction factor by: 1) determining the physiological influence degree of the physiological index on the fluid concentration of the target object, and determining a corresponding physiological correction coefficient according to the physiological influence degree; 2) determining the pathological influence degree of the pathological features on the fluid concentration of the target object, and determining a corresponding pathological correction coefficient according to the pathological influence degree; 3) determining the pharmacological influence degree of the pharmacological characteristics on the fluid concentration of the target object, and determining a corresponding pharmacological correction coefficient according to the pharmacological influence degree; 4) and determining the clinical influence degree of the post-injection state on the fluid concentration of the target object, and determining a corresponding state correction coefficient according to the clinical influence degree.
The determination process of the physiological influence degree, the pathological influence degree, the pharmacological influence degree and the clinical influence degree can be as follows: determining the influence of each parameter influence index on the fluid concentration, quantifying the influence or establishing a corresponding relation, and determining the influence as a corresponding influence degree according to the result obtained after quantification or the corresponding relation.
In the embodiment, the correction coefficient is determined according to the influence degree of the parameter influence index on the fluid concentration, so that a quantized correction coefficient can be obtained, and the corrected output parameter can be accurately obtained by correcting the basic output parameter according to the correction coefficient.
In one embodiment, the modification coefficient determination model includes a target physiological coefficient formula; before the step of inputting the index value into the pre-constructed modification coefficient determination model, the method further comprises: and searching a target physiological coefficient formula matched with the index value from a predetermined formula library to serve as the correction coefficient determination model.
Wherein, the target physiological coefficient formula refers to a formula capable of calculating a physiological correction coefficient based on the input index value. The formula library refers to a database in which formulas are recorded in a storage space of a computer device. In one embodiment, the formula library may include a physiological coefficient formula obtained by combining various parameter influence indicators. When the computer equipment acquires the index value, the matched physiological coefficient formula is searched from the formula library through the corresponding relation between the parameter influence index and the physiological coefficient formula to serve as the target physiological coefficient formula.
In one embodiment, the physiological coefficient formula may be a formula that operates on a particular physiological index. The process of obtaining the target physiological coefficient formula from the formula library may be: and determining a target physiological index corresponding to the acquired index value, searching a physiological coefficient formula constructed based on the target physiological index in a formula library, and determining the physiological coefficient formula as a target physiological coefficient formula.
In one embodiment, the specific implementation process of searching the target physiological coefficient formula matched with the index value from the predetermined formula library is as follows:
the target physiological index currently received by the computer equipment is height, weight, age and gender, and the target physiological coefficient formula containing the height, the weight, the age and the gender is searched in the formula library as follows:
wherein H represents height (cm), a represents age (yearly), and X represents gender (male X ═ 1, female X ═ 0).
It can be understood that the more physiological indexes included in the target physiological coefficient formula, the closer the physiological correction coefficient calculated according to the corresponding target physiological coefficient formula is to the ideal value.
In one embodiment, the step of inputting the index value into a pre-constructed modification coefficient determination model includes: and inputting the first index value corresponding to the physiological index into the target physiological coefficient formula to obtain a physiological correction coefficient corresponding to the physiological index.
In the above embodiment, the computer device corresponds to the formula library, and when the physiological correction coefficient needs to be determined, the matched target physiological coefficient formula can be obtained from the formula library, so that the physiological correction coefficient can be accurately output, and the correction efficiency of the basic output parameter is effectively ensured.
In an embodiment, the method further includes a process of updating the physiological correction coefficient formula, and the specific implementation process may be: and acquiring the latest standard physiological health index by accessing an index output webpage, and updating the physiological correction coefficient formula in the formula library according to the standard physiological health index.
The index output web page may be a web page having a physiological health index display function, and may be a web page of a health management institution, a medical institution, or the like. In one embodiment, the computer device may obtain the physiological health indicator of the latest publication date as the standard physiological health indicator by accessing a CGI (Common Gateway Interface) Interface of the indicator output web page.
In one embodiment, after the standard physiological health index is obtained, the computer device extracts a physiological index value corresponding to the physiological index from the standard physiological health index, and substitutes the physiological index value into the physiological correction coefficient formula to update formula parameters therein to obtain an updated physiological correction coefficient.
According to the embodiment of the invention, the formula and the use logic are upgraded according to the information issued by the authorities such as health management institutions and medical institutions and the like and the accumulation of clinical data, so that the physiological correction coefficient formula can accord with the continuously improved people's physique after the liquid output experiment is carried out on the human body model, and a liquid output mode which is more accordant with the people's physique is obtained.
In one embodiment, the target physiological coefficient formula comprises a body fat rate correction formula; the step of inputting the first index value corresponding to the physiological index into the target physiological coefficient formula to obtain the physiological correction coefficient corresponding to the physiological index includes: inputting the first index value into the body fat rate correction formula to obtain a body fat rate correction coefficient; determining the body fat rate correction coefficient as the physiological correction coefficient.
The following illustrates the formula of the body fat ratio correction factor:
the body fat rate correction coefficient formula can be:
wherein, the standard body fat rate can refer to the body fat rate published by the official.
The body fat rate correction coefficient formula can also be:
wherein the standard BMI may refer to an official published body weight height index. The body fat ratio in the above formula can be calculated by one of the following formulas:
in one embodiment, the target physiological coefficient formula is a metabolic modification formula; the step of inputting the first index value corresponding to the physiological index into the target physiological coefficient formula to obtain the physiological correction coefficient corresponding to the physiological index includes: inputting the first index value into the metabolic correction formula to obtain a metabolic correction coefficient; determining the metabolic correction factor as the physiological correction factor.
The metabolic correction factor equation is illustrated below:
the metabolic correction factor formula may be:
the basal metabolism normal value may refer to the official published basal metabolism data. And the basal metabolic number can be calculated by one of the following formulas:
for males: BMR (kJ) ═ 370+20H +52W-25A
For women: bmr (kj) -1873 +13H +39W-18A
Further, the step of calculating the physiological correction coefficient according to the body fat rate correction coefficient and the metabolic correction coefficient can be realized by the following formula:
wherein, the standard body fat and the normal value of basal metabolism can refer to the data published by the official. KFat and oilAs a body fat ratio correction factor, KSubstitute for Chinese traditional medicineFor metabolic correction factor,. DELTA.T is the body temperature change value, KtΔ is the correction intensity of the entire correction formula for the temperature correction coefficient (i.e., the correction intensity against the change in body temperature), and Δ is 1/2, i.e., the entire correctionThe strength is halved.
In one embodiment, the target physiological coefficient formula comprises a body fat rate correction formula and a metabolic correction formula; the step of inputting the first index value corresponding to the physiological index into the target physiological coefficient formula to obtain the physiological correction coefficient corresponding to the physiological index includes: inputting the first index value into the body fat rate correction formula and the metabolism correction formula respectively to obtain a body fat rate correction coefficient and a metabolism correction coefficient; and obtaining the physiological correction coefficient according to the body fat rate correction coefficient and the metabolism correction coefficient.
In one embodiment, if the physiological index includes height, weight, age and gender, the computer device finds the body fat rate correction coefficient formula and the metabolism correction coefficient formula from the formula library as the target physiological coefficient formula; respectively inputting the corresponding numerical values of the height, the weight, the age and the sex of the target object into a body fat rate correction coefficient formula and a metabolism correction coefficient formula to obtain a body fat rate correction coefficient and a metabolism correction coefficient; and calculating to obtain a physiological correction coefficient according to the body fat rate correction coefficient and the metabolism correction coefficient.
In the embodiment, the body fat rate correction coefficient and the metabolism correction coefficient of the target object are calculated through the body fat rate correction formula and the metabolism correction formula, and then the physiological correction coefficient is calculated, so that the basic output parameter can be corrected from the perspective of the body fat rate and the metabolism, the corrected output parameter can effectively adjust the body fat rate and the metabolism of the target object, and the accuracy of the corrected output parameter is ensured.
In one embodiment, in addition to determining the body fat rate correction factor and the metabolic correction factor, the computer device may also determine a body temperature correction factor to correct the base output parameter based on body temperature.
In one embodiment, the correction coefficient determination model comprises a pharmacological coefficient determination model; the step of inputting the index value into a pre-constructed modification coefficient determination model includes: inputting a second index value corresponding to the pharmacological characteristic into the pharmacological coefficient determination model; so that the pharmacological coefficient determination model determines a pharmacological characteristic value corresponding to the pharmacological characteristic from a pharmacological characteristic database according to the second index value, and determines a corresponding pharmacological correction coefficient according to the pharmacological characteristic value; wherein, the pharmacological property database contains at least one pharmacological property value of the required drug; the value of the pharmacological property is used for representing the influence degree of the pharmacological property on the blood concentration of the target object.
The pharmacological coefficient determination model is a model capable of outputting a pharmacological correction coefficient based on the input second index value, and may be a predetermined formula, a pre-trained neural network model, or the like.
The value of the pharmacological property may refer to a specific numerical value. For example: the plasma protein binding rate can be divided into three grades of high, medium and low, and the results after the three grades are quantified can be used as 3 pharmacological property values.
In one embodiment, before the inputting the second index value corresponding to the pharmacological property into the pharmacological coefficient determination model, the method further includes: acquiring the pharmacological property of at least one required medicament and a corresponding index value of the pharmacological property; the pharmacological properties include at least one of: onset time, half-life, ph, lipophilicity, hydrophilicity, organ of action, and safety threshold of the drug; and establishing the pharmacological characteristic database according to the pharmacological characteristic corresponding to the at least one required medicament and the corresponding drug efficacy characteristic index value.
In one embodiment, before the inputting the second index value corresponding to the pharmacological property into the pharmacological coefficient determination model, the method further includes: receiving a pharmacological property value corresponding to the pharmacological property of the at least one desired drug; the pharmacological characteristic value is obtained by identifying the characteristic value of the drug description data; and establishing the pharmacological property database according to the pharmacological property value.
The pharmacological property value refers to an index value corresponding to the pharmacological property, namely, a specific value corresponding to the onset time, half-life, pH value, lipophilicity, hydrophilicity, action organ, safety threshold and the like of the drug.
The medicine instruction data can refer to a medicine use instruction, and can be an electronic version (or a photo of a paper version of the medicine instruction). The terminal can recognize the pharmacological characteristics in the drug description data through an OCR (Optical Character Recognition) technology.
Wherein, the half-life period can be calculated according to the following formula:
where k represents the cancellation rate constant, which can be calculated by the following equation:
inco denotes the first dose, Inc denotes the maintenance dose, and t denotes the interval time. It can also be calculated by the following formula:
wherein C represents a volume, LTIndicating a clear rate.
The drug accumulation ratio can be calculated by the following formula:
the therapeutic index can be calculated by the following formula:
wherein ED50Representing the median lethal dose, ED50Denotes a half effective amount, ED1And ED95The same is true.
The maintenance amount can be calculated by the following formula:
wherein D is the first dose and T is the time interval between two administrations.
In the above embodiment, the computer device acquires the pharmacological characteristics and the corresponding index values of the pharmacological characteristics in various ways, and further constructs the pharmacological characteristic database. Aiming at various possible second index values, the pharmacological coefficient determining model can accurately determine the corresponding pharmacological correction coefficient, and can effectively improve the correction efficiency of the basic output parameter.
In one embodiment, the pharmacological correction factor is determined based on pharmacological properties, the basic output parameter is corrected based on pharmacokinetic properties and pharmacological properties of the drug itself, and the dosing regimen may be formulated to balance differences in the phases of action of drugs of different properties in the target subject.
In one embodiment, after the step of establishing the pharmacological property database according to the pharmacological property, the index value and the pharmacological property value corresponding to the at least one required drug, the method further comprises: acquiring pharmacological property change information of the at least one required drug; the pharmacological characteristic change information is obtained by accessing a drug information storage device; and updating the pharmacological property database according to the pharmacological property change information.
The medicine information storage device can be a medicine information storage device of a pharmacy and a medicine supervision department. Specifically, the server may be a server of each large pharmacy, a server of each medication administration, or the like.
In the above embodiment, the computer device obtains the pharmacological property change information through the drug information storage device, and updates the pharmacological property database accordingly, so that the pharmacological property database can be matched with the latest pharmacological property, the accuracy of the determined pharmacological correction coefficient is ensured, and the correction efficiency of the basic output parameter is further improved.
In one embodiment, the correction coefficient determination model comprises a pathology coefficient determination model; the step of inputting the index value into a pre-constructed modification coefficient determination model includes: inputting a third index value corresponding to the pathological sign of the target object into a pathological coefficient determination model, so that the pathological coefficient determination model determines a pathological correction coefficient corresponding to the pathological sign from a pathological sign database according to the third index value; wherein, the pathological sign database comprises the corresponding relation between the pathological signs and the pathological correction coefficients.
Wherein, the pathological features can be disease signs, target organ signs, target object drug metabolism characteristics and the like.
The pathology coefficient determination model refers to a model that can generate a pathology correction coefficient based on an input index value. The pathological coefficient determination model can be a pre-constructed formula or a pre-trained neural network model.
The pathological sign database comprises the corresponding relation between pathological features and pathological correction coefficients. And when the third index value is obtained, the computer equipment inputs the third index value into the pathological coefficient determination model, and the pathological coefficient determination model finds the matched pathological correction coefficient according to the corresponding relation.
According to the embodiment, the pathological correction coefficient is rapidly and accurately determined through the pathological coefficient determination model, and the correction efficiency of the basic output parameter can be effectively improved. In one embodiment, the computer device determines a pathological correction coefficient according to pathological characteristics such as disease signs and target organ signs, and further controls the liquid output device, so that abnormal drug metabolic manifestations of special disease signs can be corrected, and abnormal drug metabolic manifestations of special disease signs can be corrected. While maintaining ideal blood concentration, the medicament can furthest reduce the toxic and side effects of the medicament on important organs such as kidney, liver, thyroid, cardiovascular and the like.
In one embodiment, after the inputting of the third index value corresponding to the pathological sign of the target subject into the pathological coefficient determination model, the method further includes: acquiring pathological organism reaction data of the target object to the liquid to be output; and updating the pathological sign database according to the pathological organism reaction data.
The pathological organism reaction data refers to biological or chemical reaction of the target object to the liquid to be output after the liquid to be output is output to the target object.
According to the embodiment, the pathological sign database is updated according to pathological organism response data, so that the pathological sign database is always in the latest state, the determined pathological correction coefficient has higher accuracy, and the correction efficiency of the basic output parameter is ensured.
In an embodiment, determining a correction coefficient output by the model according to the correction coefficient, and performing at least one stage of correction on the basic output parameter to obtain a corrected output parameter may be: acquiring a physiological correction coefficient corresponding to the physiological index, and performing primary correction on the basic output parameter through the physiological correction coefficient to obtain a primary output parameter; obtaining a pharmacological correction coefficient corresponding to the pharmacological characteristic, and performing secondary correction on the primary output parameter through the pharmacological correction coefficient to obtain a secondary output parameter; acquiring a pathological correction coefficient corresponding to the pathological sign, and performing three-level correction on the second-level output parameter through the pathological correction coefficient to obtain a third-level output parameter; and determining a clinical correction coefficient corresponding to the clinical response characteristic, and performing four-stage correction on the three-stage output parameter according to the clinical correction coefficient to obtain the corrected output parameter.
In the embodiment, the basic output parameters are corrected in a four-stage correction mode, corrected output parameters which are as accurate as possible are obtained through correction as many times as possible, and the correction efficiency of the output parameters is ensured.
It should be noted that the process of correcting the basic output parameter may be implemented in a combined manner, for example, as shown in the above embodiment, the basic output parameter may be corrected by using all correction coefficients, or only a part of the correction coefficients may be selected and the correction order thereof may be adjusted, for example, the basic output parameter is subjected to primary correction by using a pathological correction coefficient, the basic output parameter is subjected to secondary correction by using a physiological correction coefficient, and then the basic output parameter is subjected to tertiary correction by using a clinical correction coefficient, so as to obtain a corrected output parameter.
According to the embodiment, the computer equipment can realize multi-stage correction of the basic output parameters, and the correction accuracy of the basic output parameters is ensured.
In one embodiment, the step of determining a correction coefficient of the model output according to the correction coefficient, and performing at least one stage of correction on the basic output parameter to obtain a corrected output parameter includes: acquiring a physiological correction coefficient corresponding to the physiological index, a pharmacological correction coefficient corresponding to the pharmacological characteristic and a pathological correction coefficient corresponding to the pathological sign; integrating the physiological correction coefficient, the pharmacological correction coefficient and the pathological correction coefficient to obtain a reference correction coefficient; correcting the basic output parameter according to the reference correction coefficient to obtain a reference output parameter; determining clinical correction coefficients corresponding to the clinical response characteristics; the clinical response characteristic is a response characteristic of the target object after the target object is injected with the liquid to be output; and correcting the reference output parameter according to the clinical correction coefficient to obtain the corrected output parameter.
In another embodiment, the step of determining a correction coefficient of the model output according to the correction coefficient, and performing at least one stage of correction on the basic output parameter to obtain a corrected output parameter includes: acquiring a physiological correction coefficient corresponding to the physiological index, a pharmacological correction coefficient corresponding to the pharmacological characteristic and a pathological correction coefficient corresponding to the pathological sign; integrating the physiological correction coefficient, the pharmacological correction coefficient and the pathological correction coefficient to obtain a reference correction coefficient; determining clinical correction coefficients corresponding to the clinical response characteristics; the clinical response characteristic is a response characteristic of the target object after the target object is injected with the liquid to be output; correcting the reference correction coefficient according to the clinical correction coefficient to obtain a corrected reference correction coefficient; and correcting the basic output parameter through the corrected reference correction coefficient to obtain the corrected output parameter.
The above two embodiments can be further explained in the following two ways:
1. global adjustment, (base part + correction part) scaling simultaneously;
2. and adjusting the correction part, and proportionally adjusting the basic part and the correction part.
The basic part refers to basic output parameters, and the correction part refers to correction coefficients corresponding to physiological indexes, pathological features and pharmacological characteristics. The scaling here may refer to an adjustment by a state correction factor.
In addition, the ratio at the time of adjustment may be determined within a set range, which may be +/-100%, according to the actual situation. For example, the injection amount of the syringe pump may be controlled to be 3/4, 1/2, 1/4, etc. of the initial amount.
The intelligent correction method for the liquid output parameter of the injection system provided by the embodiment further corrects the injection parameter according to the post-injection state of the target object on the basis of physiological correction, pathological correction and pharmacological correction of the basic output parameter, so that the accurate injection parameter can be obtained, the accurate control of the liquid output device is realized, and the injection effect of the liquid output device is effectively improved.
In one embodiment, the fluid output device is a syringe, the modified output parameter comprises at least one of a modified output speed, a modified output time; after the step of determining a correction coefficient output by the model according to the correction coefficient and performing at least one-stage correction on the basic output parameter to obtain a corrected output parameter, the method further comprises the following steps: and sending a medicine output instruction to a signal input interface of an injector according to the corrected output parameters so as to enable the injector to output the liquid to be output to the target object according to at least one of the corrected output speed and the corrected output time.
In the embodiment, the basic output parameters are corrected in a multi-stage mode by the computer equipment, the corrected output parameters obtained after the multi-stage correction have a good concentration control effect, and then the injector is pushed to push out liquid to be output according to the corrected output parameters, so that a target object can be effectively controlled, and the injection effect of the injector is improved.
In one embodiment, the step of obtaining a basic output parameter of the liquid to be output includes: and inputting the weight of the target object, the target medicine amount, the medicine dosage and the syringe capacity into a predetermined first basic parameter calculation formula to obtain the basic output parameter.
In another embodiment, the step of obtaining a basic output parameter of the liquid to be output includes: and inputting the weight of the target object, the target dosage and the medicine parameters into a predetermined second basic parameter calculation formula to obtain the basic output parameters.
In one embodiment, the step of obtaining a basic output parameter of the liquid to be output according to the liquid consumption characteristic of the target object includes: and determining the liquid consumption characteristics according to the weight of a target object, the target medicine amount, the medicine dosage and the syringe capacity, and inputting the liquid consumption characteristics into a predetermined first basic parameter calculation formula to obtain the basic output parameters.
In another embodiment, the step of obtaining a basic output parameter of the liquid to be output according to the liquid consumption characteristic of the target object includes: and determining the liquid consumption characteristics according to the weight of the target object, the target medicine amount and the medicine parameters, and inputting the liquid consumption characteristics into a predetermined second basic parameter calculation formula to obtain the basic output parameters.
Taking the basic output parameter as an example of the injection speed, the first basic parameter calculation formula can be realized by the following formula (1):
the second basic parameter calculation formula may be implemented by the following formula (2):
wherein F represents a base output parameter, W represents a weight (kg) of a target object, D represents a target drug amount (μ g/kg/min), V represents an injection device capacity (ml), J represents a drug dose (μ g), and C represents a drug concentration (μ g/ml).
The above formula only needs the weight of the target object and the parameters of the liquid to be output to calculate the injection speed of the injector, and is also a calculation method widely used at present. However, the method does not consider the drug metabolism difference caused by individual differences such as fat content and the like, and the target blood concentration cannot be accurately controlled, namely the injection effect is not ideal enough, so that the basic output parameter needs to be corrected.
In addition, it should be noted that the constant coefficients in the formula in the embodiment of the present invention are merely examples, and in an actual application scenario, specific values thereof may vary according to a specific scenario.
In order to further approximate the estimation result to the actual value, a corresponding operation formula may be determined according to the individual difference of the target object to obtain a corresponding correction coefficient.
In one embodiment, as shown in fig. 3, a method for intelligently modifying a fluid output parameter of an injection system is provided, which is exemplified by a computer device, and comprises the following steps:
1. the computer device receives the target subject's weight, target drug amount, drug dosage and syringe volume entered by the user via the input device, and determines the base injection parameters based on this information.
2. The computer device collects the physiological index of the target object, namely the height, the weight, the age and the sex of the target object input by the user.
Carrying out formula library operation: and determining a target physiological coefficient formula from the formula library, substituting the values corresponding to the height, the weight, the age and the sex into the target physiological coefficient formula to obtain a corresponding body temperature correction coefficient, a metabolic correction coefficient and a body fat rate correction coefficient, and determining the correction coefficients as physiological correction coefficients.
And performing primary correction on the basic injection parameter through the physiological correction coefficient to obtain a first injection parameter. The primary correction carries out comprehensive evaluation according to the physiological index of the target object, and generates corresponding individualized basic infusion parameters according to the evaluation result so as to reduce the influence of individual difference on the distribution, metabolism and discharge processes of the medicine.
3. And the computer equipment determines a pathological correction coefficient by inquiring a pathological sign database according to pathological features of the target object, such as disease signs, target organ signs, drug metabolism features and the like. And carrying out secondary correction on the first injection parameter through the pathological correction coefficient to obtain a second injection parameter. The second-level correction corrects the basic output parameters according to the pharmacological characteristics of the drug.
4. The computer equipment obtains the pharmacological characteristics of the drug to be injected, such as onset time, half-life period, plasma protein binding rate and the like, and determines a pharmacological correction coefficient by inquiring a pharmacological characteristic database. And carrying out three-stage correction on the second injection parameter through the pharmacological correction coefficient to obtain a third injection parameter. And the three-stage correction aims at pathological signs of the target object so as to perform targeted comprehensive regulation and control on the basic output parameters.
5. The computer device predicts the possible heart rate change, blood oxygen change, body temperature change and the like of the target object after the medicine is injected, and then determines the state correction coefficient. The third injection parameter is four-stage corrected by the state correction factor to obtain a fourth injection parameter, i.e. the corrected injection parameter in the previous embodiment. The four-stage correction is based on the state of the patient after injection, and the computer device can selectively control the overall intervention intensity, so that the correction efficiency of the injection parameters is improved. So as to ensure that the whole correction process is safe, visible and controllable.
6. And controlling the injector to inject the medicine to be injected to the target object based on the corrected injection parameters.
The conventional drug injection method has the following problems:
firstly, the intravenous drug injection effect is influenced by a plurality of factors, including target plasma drug concentration of the drug, injection speed, injection mode and the like; meanwhile, the injection effect is also influenced by the conditions of the injection object, such as: age, body fat condition, visceral fat condition, muscle condition, vascular regulation, metabolic condition, and the level of a specific drug metabolizing enzyme, and the like, and therefore there is no clear index of judgment between the drug injection process and the injection effect;
secondly, because of lack of reliable drug application effect indexes, most of the current drug injections adopt a constant-speed infusion mode under total amount control, and plasma drug concentration cannot be monitored, so that the drug infusion mode often adopts an experience preset scheme, and the schemes both lack objective drug action effect indexes and cannot realize targeted drug administration schemes, and the plasma concentration, the drug effect and other conditions of the injected drugs can be presumed only through some vital signs and reactions after injection;
thirdly, due to the complexity of pharmacodynamics and pharmacokinetics, the difference of physiological conditions, disease conditions and circulation conditions of an injection object, the limitation of the existing medicine efficacy monitoring technology, the limitation of people to medicine efficacy recognition, and other factors, intelligent medicine infusion cannot be realized, and an accurate personalized medicine administration scheme cannot be realized, so that the medicine infusion scheme can be only managed in a fuzzy way by experience at present, and a great amount of medicine efficacy misreading situations exist; on the other hand, even if a drug administration disaster event caused by misjudgment and misreading occurs, the related information and parameters of pharmacodynamics cannot be monitored timely and accurately, and the experience and training cannot be discovered, corrected or summarized afterwards. At present, no intelligent injection pump is mentioned in relevant guidelines including the United states, Europe and China, and the existing target-controlled infusion technology has the defects which cannot be overcome: for the action positions of some medicines (possibly heart and brain or other important organs, and the collection of samples cannot be carried out), the target blood concentration cannot be detected in real time, so that the target and control cannot be mentioned.
The injection method of the intelligent correction method based on the liquid output parameters sets the final target blood concentration (namely the target concentration) of the medicine according to the pharmacodynamics and pharmacokinetic characteristics of the medicine; basic pathophysiological conditions such as physiological characteristics, structural characteristics, pathological conditions, metabolic conditions and the like of a target object can be standardized, automatic correction of injection parameters is realized, and further a personalized injection scheme is realized, so that the target blood concentration is reached in the target object, and the target deviation of medicine use can be greatly avoided; the accuracy of evaluation and judgment of the effect of the medicament can also be improved. In addition, the technology (equipment) does not change the prior administration route, is easy to operate, is accurate and scientific, and all the used technologies are re-modeling, calculation and integration through verification technology, so that the scope which is possibly harmful to life safety and health is not involved.
It should be understood that, although the steps in the above-described flowcharts are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least a part of the steps in the above-mentioned flowcharts may include a plurality of steps or a plurality of stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of performing the steps or the stages is not necessarily performed in sequence, but may be performed alternately or alternately with other steps or at least a part of the steps or the stages in other steps.
Based on the same idea as the intelligent correction method applied to the liquid output parameter of the injection system in the above embodiment, the present invention also provides an intelligent correction device applied to the liquid output parameter of the injection system, which can be used to execute the above intelligent correction method applied to the liquid output parameter of the injection system. For ease of illustration, only those portions of the device relevant to embodiments of the present invention are shown in the schematic structural view of the embodiment of the intelligent correction device for fluid output parameters applied to an injection system, and it will be understood by those skilled in the art that the illustrated structure does not constitute a limitation of the device, and may include more or less components than those illustrated, or may combine some components, or may be arranged differently.
In one embodiment, as shown in fig. 4, an intelligent correction device 400 for fluid output parameters of an injection system is provided, which may be a part of a computer device using a software module or a hardware module, or a combination of the two modules, and specifically comprises: an index value obtaining module 401, a model input module 402, a basic parameter obtaining module 403, and a parameter modifying module 404, wherein:
an index value obtaining module 401, configured to read an index value corresponding to at least one parameter influence index from a data storage space; the parameter influence index is an index which influences the blood concentration of the target object; wherein the target object is an organism for absorbing the liquid to be output.
A model input module 402, configured to input the index value into a pre-constructed modification coefficient determination model, so that the modification coefficient determination model outputs a corresponding modification coefficient according to the input index value.
A basic parameter obtaining module 403, configured to obtain a basic output parameter of the liquid to be output.
A parameter modification module 404, configured to determine a modification coefficient output by the model according to the modification coefficient, and perform at least one stage of modification on the basic output parameter to obtain a modified output parameter; and the corrected output parameters are used for controlling the output state of the liquid output equipment to the liquid to be output.
In the above-mentioned intelligent correction device of liquid output parameter who is applied to injection system, the injection parameter that has revised that obtains through multistage correction has better fluid concentration control effect, realizes the automatic control to the syringe under the condition of the injection effect of guaranteeing the syringe, does not need artificial participation, effectively improves the injection efficiency of liquid.
In one embodiment, the liquid to be delivered is a drug to be delivered; an index value acquisition module, comprising: the influence index determining submodule is used for determining a parameter influence index; the parameter impact indicator comprises at least one of: physiological index, pathological signs, clinical response characteristics of the target subject, and pharmacological characteristics of the fluid to be output; and the index value determining submodule is used for reading an index value corresponding to at least one parameter influence index from the data storage space.
In one embodiment, the modification coefficient determination model includes a target physiological coefficient formula; the device, still include: and the model determining module is used for searching a target physiological coefficient formula matched with the index value from a predetermined formula library to serve as the correction coefficient determining model.
In one embodiment, the model input module is further configured to input the first index value corresponding to the physiological index into the target physiological coefficient formula, so as to obtain a physiological correction coefficient corresponding to the physiological index.
In one embodiment, the apparatus further comprises: and the physiological coefficient formula updating module is used for acquiring the latest standard physiological health index by accessing the index output webpage and updating the physiological coefficient formula in the formula library according to the standard physiological health index.
In one embodiment, the target physiological coefficient formula comprises a body fat rate correction formula and a metabolic correction formula; a model input module comprising: an index value input sub-module, configured to input the first index value into the body fat rate correction formula and the metabolism correction formula, respectively, to obtain a body fat rate correction coefficient and a metabolism correction coefficient; and the physiological correction coefficient calculation submodule is used for obtaining the physiological correction coefficient according to the body fat rate correction coefficient and the metabolism correction coefficient.
In one embodiment, the correction coefficient determination model comprises a pharmacological coefficient determination model; the model input module is also used for inputting a second index value corresponding to the pharmacological characteristic into the pharmacological coefficient determination model; so that the pharmacological coefficient determination model determines a pharmacological characteristic value corresponding to the pharmacological characteristic from a pharmacological characteristic database according to the second index value, and determines a corresponding pharmacological correction coefficient according to the pharmacological characteristic value; wherein, the pharmacological property database contains at least one pharmacological property value of the required drug; the value of the pharmacological property is used for representing the influence degree of the pharmacological property on the blood concentration of the target object.
In one embodiment, the apparatus further comprises: the pharmacological index value acquisition module is used for acquiring the pharmacological characteristics of at least one required medicament and corresponding pharmacological characteristic index values; the pharmacological properties include at least one of: onset time, half-life, ph, lipophilicity, hydrophilicity, organ of action, and safety threshold of the drug; and the pharmacological database construction module is used for constructing the pharmacological characteristics corresponding to the at least one required drug and the pharmacological characteristic corresponding relation between corresponding pharmacological characteristic index values, and establishing the pharmacological characteristic database according to the pharmacological characteristic corresponding relation.
In one embodiment, the apparatus further comprises: a change information acquisition module for acquiring pharmacological property change information of the at least one required drug; the pharmacological characteristic change information is obtained by accessing a drug information storage device; and the pharmacological database updating module is used for updating the pharmacological characteristic database according to the pharmacological characteristic change information.
In one embodiment, the correction coefficient determination model comprises a pathology coefficient determination model; the model input module is further used for inputting a third index value corresponding to the pathological sign of the target object into a pathological coefficient determination model, so that the pathological coefficient determination model determines a pathological correction coefficient corresponding to the pathological sign from a pathological sign database according to the third index value; wherein, the pathological sign database comprises the corresponding relation between the pathological signs and the pathological correction coefficients.
In one embodiment, the apparatus further comprises: the reaction data acquisition module is used for acquiring pathological organism reaction data of the target object to the liquid to be output; and the pathological database updating module is used for updating the pathological sign database according to the pathological organism reaction data.
In one embodiment, the parameter modification module includes: a first correction coefficient acquisition submodule for acquiring a physiological correction coefficient corresponding to the physiological index, a pharmacological correction coefficient corresponding to the pharmacological characteristic, and a pathological correction coefficient corresponding to the pathological sign; a first correction coefficient integration submodule for integrating the physiological correction coefficient, the pharmacological correction coefficient and the pathological correction coefficient to obtain a reference correction coefficient; the first output parameter correction submodule is used for correcting the basic output parameter according to the reference correction coefficient to obtain a reference output parameter; a first clinical correction coefficient determination submodule for determining a clinical correction coefficient corresponding to the clinical response characteristic; the clinical response characteristic is a response characteristic of the target object after the target object is injected with the liquid to be output; and the second output parameter correction submodule is used for correcting the reference output parameter according to the clinical correction coefficient to obtain the corrected output parameter.
In one embodiment, the parameter modification module further includes: a second correction coefficient obtaining submodule, configured to obtain a physiological correction coefficient corresponding to the physiological index, a pharmacological correction coefficient corresponding to the pharmacological characteristic, and a pathological correction coefficient corresponding to the pathological sign; a second correction coefficient integration submodule for integrating the physiological correction coefficient, the pharmacological correction coefficient and the pathological correction coefficient to obtain a reference correction coefficient; the second clinical correction coefficient determining submodule is used for determining the clinical correction coefficient corresponding to the clinical response characteristic; the clinical response characteristic is a response characteristic of the target object after the target object is injected with the liquid to be output; the correction coefficient correction submodule is used for correcting the reference correction coefficient according to the clinical correction coefficient to obtain a corrected reference correction coefficient; and the third output parameter correction submodule is used for correcting the basic output parameter through the corrected reference correction coefficient to obtain the corrected output parameter.
In one embodiment, the fluid output device is a syringe, the modified output parameter comprises at least one of a modified output speed, a modified output time; the device, still include: and the injector control module is used for sending a medicine output instruction to a signal input interface of the injector according to the corrected output parameter so as to enable the injector to output the liquid to be output to the target object according to at least one of the corrected output speed and the corrected output time.
In one embodiment, the basic parameter obtaining module is further configured to input the weight of the target subject, the target amount of the drug, the dosage of the drug, and the syringe capacity into a predetermined first basic parameter calculation formula to obtain the basic output parameter.
In one embodiment, the basic parameter acquiring module is further configured to input the weight of the target object, the target drug amount, and the drug parameter into a predetermined second basic parameter calculation formula to obtain the basic output parameter.
For the specific definition of the intelligent correction device applied to the liquid output parameter of the injection system, reference may be made to the above definition of the intelligent correction method applied to the liquid output parameter of the injection system, and details are not repeated here. The various modules of the above described intelligent correction of fluid output parameters applied to an injection system may be implemented in whole or in part by software, hardware, and combinations thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as shown in fig. 5. The computer device includes a processor, a memory, a communication interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The communication interface of the computer device is used for carrying out wired or wireless communication with an external terminal, and the wireless communication can be realized through WIFI, an operator network, NFC (near field communication) or other technologies. The computer program is executed by a processor to implement a method for intelligent correction of fluid output parameters applied to an injection system. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, a key, a track ball or a touch pad arranged on the shell of the computer equipment, an external keyboard, a touch pad or a mouse and the like.
Those skilled in the art will appreciate that the architecture shown in fig. 5 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer device is further provided, which includes a memory and a processor, the memory stores a computer program, and the processor implements the steps of the above method embodiments when executing the computer program.
In an embodiment, a computer-readable storage medium is provided, in which a computer program is stored which, when being executed by a processor, carries out the steps of the above-mentioned method embodiments.
In one embodiment, a computer program product or computer program is provided that includes computer instructions stored in a computer-readable storage medium. The computer instructions are read by a processor of a computer device from a computer-readable storage medium, and the computer instructions are executed by the processor to cause the computer device to perform the steps in the above-mentioned method embodiments.
It will be understood by those skilled in the art that all or part of the processes of the methods of the above embodiments may be implemented by a computer program, which is stored in a computer readable storage medium and sold or used as a stand-alone product. More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via for instance optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.
Based on the same idea as the intelligent correction method applied to the liquid output parameter of the injection system in the above-described embodiment, the present invention also provides an injection system, which can be used to perform the above-described intelligent correction method applied to the liquid output parameter of the injection system. For ease of illustration, only those portions of the injection system that are relevant to embodiments of the present invention are shown in the schematic view of the injection system, and those skilled in the art will appreciate that the structure shown in the drawings does not constitute a limitation of the injection system, and may include more or less components than those shown, or some components in combination, or a different arrangement of components.
In one embodiment, as shown in fig. 6, there is provided an injection system 600 comprising a controller 601 and an injector 602; the injector is used for containing liquid to be output; the controller is connected with the injector network.
The controller may be implemented as a stand-alone server or as a server cluster of multiple servers. In addition, the controller may be replaced with a terminal, which may be, but is not limited to, various personal computers, notebook computers, smart phones, tablet computers, and portable wearable devices. On the other hand, the injector may be, but is not limited to, various types of injectors, the number of which may be 1, 2, or even more, and the controller may selectively control the injectors. In some embodiments, the syringe 602 may be replaced with a needle, tubing, or other device having fluid transfer capabilities.
In one embodiment, the controller and the injector may communicate over a network.
The controller 601 is configured to: reading an index value corresponding to at least one parameter influence index from a data storage space; the parameter influence index is an index which influences the blood concentration of the target object; wherein the target object is an organism for absorbing the liquid to be output; inputting the index value into a pre-constructed correction coefficient determination model so that the correction coefficient determination model outputs a corresponding correction coefficient according to the input index value; acquiring basic output parameters of liquid to be output; determining a correction coefficient output by the model according to the correction coefficient, and performing at least one-stage correction on the basic output parameter to obtain a corrected output parameter; and sending a medicine output command to a signal input interface of the injector according to the corrected output parameters and the corrected output parameters.
The injector 602 is configured to: and injecting the liquid to be output to the target object according to the corrected output parameters under the triggering of the medicine output instruction.
Wherein, the injector can also be referred to as a syringe pump. The syringe pump may be, but is not limited to, a micro syringe pump, an industrial syringe pump, a medical syringe pump.
In the injection system, the controller determines a correction coefficient based on an index value corresponding to the parameter influence index, corrects the basic output parameter based on the correction coefficient to obtain a corrected output parameter which can be used for controlling the output state of the liquid output equipment to the liquid to be output, and the injector injects the liquid to be output to the target object based on the corrected output parameter. The corrected injection parameters obtained through multi-stage correction have a good fluid concentration control effect, automatic control over the injector is achieved under the condition that the injection effect of the injector is guaranteed, manual participation is not needed, and the injection efficiency of liquid is effectively improved.
In one embodiment, the liquid to be delivered is a drug to be delivered; the controller is further configured to: determining a parameter influence index; the parameter impact indicator comprises at least one of: physiological index, pathological signs, clinical response characteristics of the target subject, and pharmacological characteristics of the fluid to be output; and reading an index value corresponding to at least one parameter influence index from a data storage space.
In one embodiment, the modification coefficient determination model includes a target physiological coefficient formula; the controller is further configured to: and searching a target physiological coefficient formula matched with the index value from a predetermined formula library to serve as the correction coefficient determination model.
In one embodiment, the controller is further configured to: inputting a first index value corresponding to the physiological index into the target physiological coefficient formula to obtain a physiological correction coefficient corresponding to the physiological index; the physiological index includes at least one of: gender, age, height, weight, body fat content, metabolic index and body temperature change.
In one embodiment, the correction coefficient determination model comprises a pharmacological coefficient determination model; the controller is further configured to: inputting a second index value corresponding to the pharmacological characteristic into the pharmacological coefficient determination model; so that the pharmacological coefficient determination model determines a pharmacological characteristic value corresponding to the pharmacological characteristic from a pharmacological characteristic database according to the second index value, and determines a corresponding pharmacological correction coefficient according to the pharmacological characteristic value; wherein, the pharmacological property database contains at least one pharmacological property value of the required drug; the value of the pharmacological property is used for representing the influence degree of the pharmacological property on the blood concentration of the target object.
In one embodiment, the correction coefficient determination model comprises a pathology coefficient determination model; the controller is further configured to: inputting a third index value corresponding to the pathological sign of the target object into a pathological coefficient determination model, so that the pathological coefficient determination model determines a pathological correction coefficient corresponding to the pathological sign from a pathological sign database according to the third index value; the pathological sign database comprises a corresponding relation between pathological signs and pathological correction coefficients, and the pathological signs comprise at least one of the following items: target disorders, target organ lesions, critical patient pharmacokinetic profiles, neonatal pharmacokinetic profiles and multi-condition combined drug metabolic profiles.
In one embodiment, the controller is further configured to: acquiring a physiological correction coefficient corresponding to the physiological index, a pharmacological correction coefficient corresponding to the pharmacological characteristic and a pathological correction coefficient corresponding to the pathological sign; integrating the physiological correction coefficient, the pharmacological correction coefficient and the pathological correction coefficient to obtain a reference correction coefficient; correcting the basic output parameter according to the reference correction coefficient to obtain a reference output parameter; determining clinical correction coefficients corresponding to the clinical response characteristics; the clinical response characteristic is a response characteristic of the target object after the target object is injected with the liquid to be output; and correcting the reference output parameter according to the clinical correction coefficient to obtain the corrected output parameter.
For specific limitations of the injection system, reference may be made to the above limitations of the intelligent correction method applied to the fluid output parameter of the injection system, which are not described in detail herein. The controller in the injection system may be embedded in hardware or independent from the processor in the computer device, or may be stored in software in the memory of the computer device, so that the processor can call the above operations.
It should be understood that portions of the present invention may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
The terms "comprises" and "comprising," and any variations thereof, of embodiments of the present invention are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or (module) elements is not limited to only those steps or elements but may alternatively include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-described examples merely represent several embodiments of the present invention and should not be construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (24)
1. An intelligent correction method applied to a liquid output parameter of an injection system is characterized by being applied to a computer device and comprising the following steps:
reading an index value corresponding to at least one parameter influence index from a data storage space; the parameter influence index is an index which influences the blood concentration of the target object; wherein the target object is an organism for absorbing the liquid to be output;
inputting the index value into a pre-constructed correction coefficient determination model so that the correction coefficient determination model outputs a corresponding correction coefficient according to the input index value;
acquiring basic output parameters of liquid to be output;
determining a correction coefficient output by the model according to the correction coefficient, and performing at least one-stage correction on the basic output parameter to obtain a corrected output parameter; and the corrected output parameters are used for controlling the output state of the liquid output equipment to the liquid to be output.
2. The method of claim 1, wherein the liquid to be delivered is a drug to be delivered;
the step of reading an index value corresponding to at least one parameter influence index from the data storage space includes:
determining a parameter influence index; the parameter impact indicator comprises at least one of: physiological index, pathological signs, clinical response characteristics of the target subject, and pharmacological characteristics of the fluid to be output;
and reading an index value corresponding to at least one parameter influence index from a data storage space.
3. The method of claim 2, wherein the correction coefficient determination model comprises a target physiological coefficient formula;
before the step of inputting the index value into the pre-constructed modification coefficient determination model, the method further comprises:
and searching a target physiological coefficient formula matched with the index value from a predetermined formula library to serve as the correction coefficient determination model.
4. The method of claim 3, wherein the step of inputting the index value into a pre-constructed modification coefficient determination model comprises:
and inputting the first index value corresponding to the physiological index into the target physiological coefficient formula to obtain a physiological correction coefficient corresponding to the physiological index.
5. The method of claim 3, further comprising:
and acquiring the latest standard physiological health index by accessing an index output webpage, and updating the physiological coefficient formula in the formula library according to the standard physiological health index.
6. The method of claim 4, wherein the target physiological coefficient formula comprises a body fat rate correction formula and a metabolic correction formula;
the step of inputting the first index value corresponding to the physiological index into the target physiological coefficient formula to obtain the physiological correction coefficient corresponding to the physiological index includes:
inputting the first index value into the body fat rate correction formula and the metabolism correction formula respectively to obtain a body fat rate correction coefficient and a metabolism correction coefficient;
and obtaining the physiological correction coefficient according to the body fat rate correction coefficient and the metabolism correction coefficient.
7. The method according to claim 2, wherein the correction coefficient determination model includes a pharmacological coefficient determination model;
the step of inputting the index value into a pre-constructed modification coefficient determination model includes:
inputting a second index value corresponding to the pharmacological characteristic into the pharmacological coefficient determination model; so that the pharmacological coefficient determination model determines a pharmacological characteristic value corresponding to the pharmacological characteristic from a pharmacological characteristic database according to the second index value, and determines a corresponding pharmacological correction coefficient according to the pharmacological characteristic value; wherein, the pharmacological property database contains at least one pharmacological property value of the required drug; the value of the pharmacological property is used for representing the influence degree of the pharmacological property on the blood concentration of the target object.
8. The method according to claim 7, wherein before the inputting the second index value corresponding to the pharmacological property into the pharmacological coefficient determination model, the method further comprises:
acquiring the pharmacological property of at least one required medicament and a corresponding index value of the pharmacological property; the pharmacological properties include at least one of: onset time, half-life, ph, lipophilicity, hydrophilicity, organ of action, and safety threshold of the drug;
and constructing a pharmacological characteristic corresponding relation between the pharmacological characteristics corresponding to the at least one required medicament and the corresponding pharmacological characteristic index values, and establishing the pharmacological characteristic database according to the pharmacological characteristic corresponding relation.
9. The method according to claim 8, wherein said step of constructing a pharmacological property correspondence between the corresponding pharmacological property of said at least one desired drug and the corresponding pharmacological property index value, and building said database of pharmacological properties based on said pharmacological property correspondence, further comprises:
acquiring pharmacological property change information of the at least one required drug; the pharmacological characteristic change information is obtained by accessing a drug information storage device;
and updating the pharmacological property database according to the pharmacological property change information.
10. The method of claim 2, wherein the correction coefficient determination model comprises a pathology coefficient determination model;
the step of inputting the index value into a pre-constructed modification coefficient determination model includes:
inputting a third index value corresponding to the pathological sign of the target object into a pathological coefficient determination model, so that the pathological coefficient determination model determines a pathological correction coefficient corresponding to the pathological sign from a pathological sign database according to the third index value; wherein, the pathological sign database comprises the corresponding relation between the pathological signs and the pathological correction coefficients.
11. The method according to claim 10, wherein after inputting the third index value corresponding to the pathological sign of the target subject into the pathological coefficient determination model, the method further comprises:
acquiring pathological organism reaction data of the target object to the liquid to be output;
and updating the pathological sign database according to the pathological organism reaction data.
12. The method according to any one of claims 2 to 11, wherein the step of determining a correction factor for the model output based on the correction factor, and performing at least one stage of correction on the base output parameter to obtain a corrected output parameter comprises:
acquiring a physiological correction coefficient corresponding to the physiological index, a pharmacological correction coefficient corresponding to the pharmacological characteristic and a pathological correction coefficient corresponding to the pathological sign;
integrating the physiological correction coefficient, the pharmacological correction coefficient and the pathological correction coefficient to obtain a reference correction coefficient;
correcting the basic output parameter according to the reference correction coefficient to obtain a reference output parameter;
determining clinical correction coefficients corresponding to the clinical response characteristics; the clinical response characteristic is a response characteristic of the target object after the target object is injected with the liquid to be output;
and correcting the reference output parameter according to the clinical correction coefficient to obtain the corrected output parameter.
13. The method of any of claims 2 to 11, wherein the liquid output device is a syringe and the modified output parameter comprises at least one of a modified output speed, a modified output time;
after the step of determining a correction coefficient output by the model according to the correction coefficient and performing at least one-stage correction on the basic output parameter to obtain a corrected output parameter, the method further comprises the following steps:
and sending a medicine output instruction to a signal input interface of an injector according to the corrected output parameters so as to enable the injector to output the liquid to be output to the target object according to at least one of the corrected output speed and the corrected output time.
14. The method according to any one of claims 2 to 11, wherein the step of obtaining a base output parameter of the liquid to be output comprises:
inputting the weight of a target object, the target medicine amount, the medicine dosage and the syringe capacity into a predetermined first basic parameter calculation formula to obtain a basic output parameter;
or the like, or, alternatively,
and determining and inputting the weight of the target object, the target dosage and the medicine parameters into a predetermined second basic parameter calculation formula to obtain the basic output parameters.
15. An intelligent correction device applied to a liquid output parameter of an injection system, which is applied to a computer device, comprises:
the index value acquisition module is used for reading an index value corresponding to at least one parameter influence index from the data storage space; the parameter influence index is an index which influences the blood concentration of the target object; wherein the target object is an organism for absorbing the liquid to be output;
the model input module is used for inputting the index value into a pre-constructed correction coefficient determination model so that the correction coefficient determination model outputs a corresponding correction coefficient according to the input index value;
the basic parameter acquisition module is used for acquiring basic output parameters of the liquid to be output;
the parameter correction module is used for determining a correction coefficient output by the model according to the correction coefficient and performing at least one-stage correction on the basic output parameter to obtain a corrected output parameter; and the corrected output parameters are used for controlling the output state of the liquid output equipment to the liquid to be output.
16. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method of any of claims 1 to 14.
17. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 14.
18. An injection system comprising a controller and an injector; the injector is used for containing liquid to be output; the controller is connected with the injector network;
the controller is configured to: reading an index value corresponding to at least one parameter influence index from a data storage space; the parameter influence index is an index which influences the blood concentration of the target object; wherein the target object is an organism for absorbing the liquid to be output; inputting the index value into a pre-constructed correction coefficient determination model so that the correction coefficient determination model outputs a corresponding correction coefficient according to the input index value; acquiring basic output parameters of liquid to be output; determining a correction coefficient output by the model according to the correction coefficient, and performing at least one-stage correction on the basic output parameter to obtain a corrected output parameter; sending a medicine output instruction to a signal input interface of the injector according to the corrected output parameters;
the syringe is used for: and injecting the liquid to be output to the target object according to the corrected output parameters under the triggering of the medicine output instruction.
19. The injection system of claim 18, wherein the liquid to be delivered is a drug to be delivered;
the controller is further configured to:
determining a parameter influence index; the parameter impact indicator comprises at least one of: physiological index, pathological signs, clinical response characteristics of the target subject, and pharmacological characteristics of the fluid to be output;
and reading an index value corresponding to at least one parameter influence index from a data storage space.
20. The injection system of claim 19, wherein the correction coefficient determination model comprises a target physiological coefficient formula;
the controller is further configured to:
and searching a target physiological coefficient formula matched with the index value from a predetermined formula library to serve as the correction coefficient determination model.
21. The injection system of claim 20, wherein the controller is further configured to:
inputting a first index value corresponding to the physiological index into the target physiological coefficient formula to obtain a physiological correction coefficient corresponding to the physiological index; the physiological index includes at least one of: gender, age, height, weight, body fat content, metabolic index and body temperature change.
22. The injection system of claim 19, wherein the correction coefficient determination model comprises a pharmacologic coefficient determination model;
the controller is further configured to:
inputting a second index value corresponding to the pharmacological characteristic into the pharmacological coefficient determination model; so that the pharmacological coefficient determination model determines a pharmacological characteristic value corresponding to the pharmacological characteristic from a pharmacological characteristic database according to the second index value, and determines a corresponding pharmacological correction coefficient according to the pharmacological characteristic value; wherein, the pharmacological property database contains at least one pharmacological property value of the required drug; the value of the pharmacological property is used for representing the influence degree of the pharmacological property on the blood concentration of the target object.
23. The injection system of claim 19, wherein the correction coefficient determination model comprises a pathology coefficient determination model;
the controller is further configured to:
inputting a third index value corresponding to the pathological sign of the target object into a pathological coefficient determination model, so that the pathological coefficient determination model determines a pathological correction coefficient corresponding to the pathological sign from a pathological sign database according to the third index value; wherein, the pathological sign database comprises the corresponding relation between pathological signs and pathological correction coefficients; the pathological signs include at least one of: target disorders, target organ lesions, critical patient pharmacokinetic profiles, neonatal pharmacokinetic profiles and multi-condition combined drug metabolic profiles.
24. The injection system of any one of claims 19 to 23, wherein the controller is further configured to:
acquiring a physiological correction coefficient corresponding to the physiological index, a pharmacological correction coefficient corresponding to the pharmacological characteristic and a pathological correction coefficient corresponding to the pathological sign;
integrating the physiological correction coefficient, the pharmacological correction coefficient and the pathological correction coefficient to obtain a reference correction coefficient;
correcting the basic output parameter according to the reference correction coefficient to obtain a reference output parameter;
determining clinical correction coefficients corresponding to the clinical response characteristics; the clinical response characteristic is a response characteristic of the target object after the target object is injected with the liquid to be output;
and correcting the reference output parameter according to the clinical correction coefficient to obtain the corrected output parameter.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116504413A (en) * | 2023-04-11 | 2023-07-28 | 长沙市妇幼保健院(长沙市妇幼保健计划生育服务中心) | Artificial intelligence anesthesia management system |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN2247350Y (en) * | 1995-09-18 | 1997-02-12 | 广州军区广州总医院 | Blood medicine concentration controller for transfusion pump |
| WO1997034648A1 (en) * | 1996-03-18 | 1997-09-25 | Masson Jean Pierre | Apparatus for controlling an intravenous injection |
| US20040064040A1 (en) * | 2002-09-26 | 2004-04-01 | Kazumasa Masuda | Liquid injector for injecting contrast medium at variable rate into a subject who is to be imaged by imaging diagnostic apparatus |
| CN102512186A (en) * | 2004-11-16 | 2012-06-27 | 梅德拉股份有限公司 | Modeling of pharmaceutical propagation |
| CN103735261A (en) * | 2013-12-05 | 2014-04-23 | 北京思路高医疗科技有限公司 | Brain electricity monitoring sedation depth close loop control injection pump device |
| CN103751874A (en) * | 2014-01-21 | 2014-04-30 | 山东大学齐鲁儿童医院 | System for improving metering accuracy of newborn intravenous nutrition injection |
| CN104582596A (en) * | 2012-07-10 | 2015-04-29 | 贝克顿迪金森法国两合公司 | Integrated injection system and communication device |
| WO2018070771A1 (en) * | 2016-10-11 | 2018-04-19 | 서울대학교병원 | Method for injecting drug into patient using infusion pump, server and computer-readable recording medium |
| US20190326002A1 (en) * | 2018-04-23 | 2019-10-24 | Diane R. MOULD | Systems and methods for modifying adaptive dosing regimens |
-
2020
- 2020-11-12 CN CN202011262221.8A patent/CN112309539B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN2247350Y (en) * | 1995-09-18 | 1997-02-12 | 广州军区广州总医院 | Blood medicine concentration controller for transfusion pump |
| WO1997034648A1 (en) * | 1996-03-18 | 1997-09-25 | Masson Jean Pierre | Apparatus for controlling an intravenous injection |
| US20040064040A1 (en) * | 2002-09-26 | 2004-04-01 | Kazumasa Masuda | Liquid injector for injecting contrast medium at variable rate into a subject who is to be imaged by imaging diagnostic apparatus |
| CN102512186A (en) * | 2004-11-16 | 2012-06-27 | 梅德拉股份有限公司 | Modeling of pharmaceutical propagation |
| CN104582596A (en) * | 2012-07-10 | 2015-04-29 | 贝克顿迪金森法国两合公司 | Integrated injection system and communication device |
| CN103735261A (en) * | 2013-12-05 | 2014-04-23 | 北京思路高医疗科技有限公司 | Brain electricity monitoring sedation depth close loop control injection pump device |
| CN103751874A (en) * | 2014-01-21 | 2014-04-30 | 山东大学齐鲁儿童医院 | System for improving metering accuracy of newborn intravenous nutrition injection |
| WO2018070771A1 (en) * | 2016-10-11 | 2018-04-19 | 서울대학교병원 | Method for injecting drug into patient using infusion pump, server and computer-readable recording medium |
| US20190326002A1 (en) * | 2018-04-23 | 2019-10-24 | Diane R. MOULD | Systems and methods for modifying adaptive dosing regimens |
Non-Patent Citations (1)
| Title |
|---|
| 杜毅: "静脉输液不良事件与四种影响因素之间相关性分析研究", 《中国优秀硕士学位论文全文数据库医药卫生科技辑》, no. 7, pages 64 - 65 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116504413A (en) * | 2023-04-11 | 2023-07-28 | 长沙市妇幼保健院(长沙市妇幼保健计划生育服务中心) | Artificial intelligence anesthesia management system |
| CN116504413B (en) * | 2023-04-11 | 2024-04-26 | 长沙市妇幼保健院(长沙市妇幼保健计划生育服务中心) | Artificial intelligence anesthesia management system |
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