CN108399951B - Breathing machine-related pneumonia decision-making assisting method, device, equipment and medium - Google Patents
Breathing machine-related pneumonia decision-making assisting method, device, equipment and medium Download PDFInfo
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Abstract
The embodiment of the invention discloses a breathing machine-related pneumonia decision-making auxiliary method, a breathing machine-related pneumonia decision-making auxiliary device, breathing machine-related pneumonia decision-making equipment and a breathing machine-related pneumonia decision-making medium, wherein the breathing machine-related pneumonia decision-making auxiliary method comprises the following steps: receiving patient sign data sent by sign monitoring equipment; acquiring patient inspection data through a hospital management system; and generating auxiliary diagnosis information according to the patient sign data, the patient inspection data and a diagnosis and treatment model obtained by pre-training, wherein the diagnosis and treatment model is obtained by training according to the corpus of the ventilator-associated pneumonia. The method for assisting the decision-making of the ventilator-associated pneumonia provided by the embodiment of the invention can provide the assistant decision-making information of 'from pre-treatment to treatment' of the ventilator-associated pneumonia for clinical medical staff, diagnose and treat the ventilator-associated pneumonia of a patient timely and effectively, improve the diagnosis efficiency of the ventilator-associated pneumonia, effectively reduce medical errors, improve the medical care quality and save a large amount of cost for hospitals.
Description
Technical Field
The embodiment of the invention relates to the field of medical instruments, in particular to a breathing machine-related pneumonia decision-making assisting method, a breathing machine-related pneumonia decision-making assisting device, breathing machine-related pneumonia decision-making equipment and a breathing machine-related pneumonia decision-making medium.
Background
Ventilator Associated Pneumonia (VAP), which is pneumonia of a patient subjected to tracheal intubation or tracheotomy after 48 hours of mechanical ventilation, is one of the most common nosocomial acquired infections of patients in the critical medicine department, and has a high incidence and fatality rate reported at home and abroad by VAP.
At present, after a patient receives mechanical ventilation for 48 hours, by collecting detection data of the patient, clinical staff judges whether the patient is ill according to the detection data of the patient, and after the patient is determined to be ill, the clinical staff determines treatment measures according to self experience and the ill condition of the patient.
Therefore, the current VAP diagnosis mode is passive, the treatment mode is easily influenced by the experience of medical staff, and the diagnosis and treatment effects are poor.
Disclosure of Invention
In view of the above problems, embodiments of the present invention provide a method, an apparatus, a device, and a medium for assisting a decision-making of ventilator-associated pneumonia, so as to provide assistant decision-making information of VAP from "prognosis to treatment" for clinical medical staff, and diagnose and treat VAP of a patient timely and effectively.
In a first aspect, an embodiment of the present invention provides a method for assisting a decision of ventilator-associated pneumonia, including:
receiving patient sign data sent by sign monitoring equipment;
acquiring patient inspection data through a hospital management system;
and generating auxiliary diagnosis information according to the patient sign data, the patient inspection data and a diagnosis and treatment model obtained by pre-training, wherein the diagnosis and treatment model is obtained by training according to the corpus of the ventilator-associated pneumonia.
In a second aspect, an embodiment of the present invention further provides a ventilator-associated pneumonia decision assistance device, including:
the physical sign data acquisition module is used for receiving the physical sign data of the patient sent by the physical sign monitoring equipment;
the examination data acquisition module is used for acquiring patient examination data through a hospital management system;
and the diagnosis information generation module is used for generating auxiliary diagnosis information according to the patient sign data, the patient inspection data and a diagnosis and treatment model obtained by pre-training, wherein the diagnosis and treatment model is obtained by training according to the linguistic data of the ventilator-associated pneumonia.
In a third aspect, an embodiment of the present invention further provides a ventilator-associated pneumonia decision assistance apparatus, where the apparatus includes:
one or more processors;
storage means for storing one or more programs;
when executed by the one or more processors, cause the one or more processors to implement a ventilator-associated pneumonia decision assistance method as provided by any embodiment of the invention.
In a fourth aspect, embodiments of the present invention further provide a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements a method for assisting a decision making of ventilator-associated pneumonia, according to any of the embodiments of the present invention.
The embodiment of the invention receives the patient sign data sent by the sign monitoring equipment; acquiring patient inspection data through a hospital management system; and the auxiliary diagnosis information is generated according to the patient sign data, the patient inspection data and the diagnosis and treatment model obtained by pre-training according to the corpus of the ventilator-associated pneumonia, the auxiliary decision information of 'from pre-treatment to treatment' of the ventilator-associated pneumonia is provided for clinical medical staff, the diagnosis and treatment of the ventilator-associated pneumonia of the patient are timely and effectively carried out, the diagnosis efficiency of the ventilator-associated pneumonia is improved, the medical errors are effectively reduced, the medical care quality is improved, and a large amount of cost is saved for hospitals.
Drawings
FIG. 1 is a flow chart of a method for assisting in the decision-making of ventilator-associated pneumonia according to an embodiment of the present invention;
FIG. 2 is a flow chart of a method for assisting in determining ventilator-associated pneumonia according to a second embodiment of the present invention;
FIG. 3 is a flow chart of a method for assisting in the decision-making of ventilator-associated pneumonia according to a third embodiment of the present invention;
fig. 4 is a schematic structural diagram of a ventilator-associated pneumonia decision assistance apparatus according to a fourth embodiment of the present invention;
fig. 5 is a schematic structural diagram of an auxiliary device for determining ventilator-associated pneumonia according to a fifth embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.
Example one
Fig. 1 is a flowchart of a method for assisting a decision of ventilator-associated pneumonia according to a first embodiment of the present invention, which can be applied to diagnosis, prevention and treatment of ventilator-associated pneumonia in a patient. The method may be performed by a ventilator-associated pneumonia decision aid, which may be implemented in software and/or hardware, for example, the ventilator-associated pneumonia decision aid may be configured in a ventilator-associated pneumonia decision aid. As shown in fig. 1, the method specifically includes:
and S110, receiving patient sign data sent by the physical sign monitoring equipment.
The patient sign data can reflect the vital signs of the patient and reflect the health condition of the patient. Optionally, the vital sign data includes respiration, body temperature, pulse and blood pressure, and abnormalities in the vital sign data can cause serious or fatal diseases, and certain diseases can also cause changes in the vital sign data. Among them, body temperature is one of the main bases for clinical diagnosis of ventilator-associated pneumonia.
In this embodiment, the patient data acquisition module acquires patient sign data, and the time interval for each sign monitoring device to send the patient sign data to the patient data acquisition module can be preset. For example, the time interval can be set to 5 minutes, and each vital signs monitoring device sends the current patient vital signs data to the patient data acquisition module every 5 minutes.
Optionally, after acquiring the patient sign data, the patient data acquisition module stores the current patient sign data in a preset format to form patient historical sign data. The historical sign data of the patient can be divided into non-infection data and infection data according to the current patient state, so that auxiliary diagnosis information can be formed according to the historical sign data of the patient in the subsequent treatment process.
And S120, acquiring patient inspection data through a hospital management system.
In addition to the vital sign data, additional test data from the patient may be acquired to aid in the diagnosis of ventilator-associated pneumonia. Generally, after a patient carries out various detections, medical staff can input detection results into a hospital management system, so that the medical staff in different departments can acquire various detection data of the patient through the hospital management system, and meanwhile, the patient can be conveniently referred to in a subsequent treatment process.
Optionally, the patient examination data is acquired by a hospital management information acquisition module. After patient sign data sent by the sign monitoring equipment is received, the hospital management information acquisition module sends a patient inspection data acquisition request to the hospital management system, wherein the patient inspection data acquisition request comprises the ID of a patient and the name of an inspection project required to be acquired, and the hospital management system sends corresponding various items of inspection data of the patient to the hospital management information acquisition module according to the patient ID and the name of the inspection project in the inspection data acquisition request.
In this embodiment, the patient test data includes patient blood test results, endotracheal aspirate culture results, lung CT imaging results, microbiological diagnosis results, biomarker results for infection, differential analysis of infection and colonization, blood culture results, culture results for pleural effusion, clinical lung infection scores, and the like.
Optionally, the hospital management information acquisition module may further obtain drug management data, such as antibacterial drug management data and/or multiple drug-resistant bacteria management data, through a hospital management system, so as to facilitate selection of a suitable drug according to the drug management data when the auxiliary diagnostic information is subsequently determined.
S130, generating auxiliary diagnosis information according to the patient sign data, the patient inspection data and a diagnosis and treatment model obtained through pre-training, wherein the diagnosis and treatment model is obtained through corpus training of ventilator-associated pneumonia.
In this embodiment, the analyzer may analyze the patient sign data acquired by the patient data acquisition module and the patient examination data acquired by the hospital management information acquisition module according to a diagnosis and treatment model obtained through pre-training, so as to generate auxiliary diagnosis information, and further provide risk prediction information, prevention auxiliary decision information, and auxiliary decision information for treating and controlling infected patients for medical staff.
Optionally, the diagnosis and treatment model is obtained by training the VAP rule engine module according to the corpus of ventilator-associated pneumonia. Wherein, the corpus of the ventilator-associated pneumonia can be acquired through the Internet. For example, the existing scientific research literature related to the ventilator-associated pneumonia in the internet is captured through a big data mining program, the data of infection risk factors and treatment means in the scientific research literature are structured, meanwhile, a mathematical algorithm is applied to count the above contents, and a diagnosis and treatment rule of the ventilator-associated pneumonia is extracted to obtain a corresponding diagnosis and treatment model. The mathematical algorithm may include classification, statistical or machine learning algorithms such as logistic regression binary classification, GBDT binary classification, K nearest neighbor, logistic regression multi-classification, random forest, naive bayes, collaborative filtering, confusion matrix, pearson's coefficient, histogram, T test, chi-square test, and/or discrete value feature analysis. The linguistic data related to the ventilator-associated pneumonia in the internet are structurally extracted through various classification, statistics and/or machine learning algorithms to generate a diagnosis and treatment model, so that the diagnosis and treatment model is more accurate, and auxiliary diagnosis information output by the diagnosis and treatment model is more accurate. With the update of scientific research documents of the pneumonia related to the breathing machine on the Internet, a corresponding diagnosis and treatment model can be generated in time, so that the diagnosis and treatment of the pneumonia related to the breathing machine are not limited by personal experience of medical staff.
Optionally, in addition to obtaining the diagnosis and treatment model through training, the medical staff may also construct a part of rules in the diagnosis and treatment model according to their own experience, and generate the diagnosis and treatment model together with the diagnosis and treatment rules constructed by the corpus related to the ventilator-associated pneumonia.
It should be noted that the method for assisting in decision making of ventilator associated pneumonia provided by the embodiment of the present invention enables medical staff to conveniently perform interactive operation with a hospital database end through a form displayed on a web page and an input interface, facilitates a hospital to perform daily diagnosis, data analysis and generation of auxiliary diagnosis information on ventilator associated pneumonia of a patient, and is advantageous to avoid problems of data confusion and the like caused by misoperation and the like by stripping and storing information such as patient sign data, patient test data and the like based on a browser/server mode of a NET frame.
The embodiment of the invention utilizes highly customized human-computer functions and big data mining and machine learning technologies to cooperate with a flexible diagnosis and treatment model to form an auxiliary decision system, is applied to assisting medical staff to collect data of the relevant pneumonia of the breathing machine, carry out clinical decision of the relevant pneumonia of the breathing machine and manage medical behaviors, provides auxiliary decision information of 'from the advance to the treatment' of the relevant pneumonia of the breathing machine for the clinical medical staff, and effectively diagnoses and treats the relevant pneumonia of the breathing machine for patients in time, thereby improving the diagnosis efficiency of the relevant pneumonia of the breathing machine, effectively reducing medical errors, improving the quality of medical care and saving a large amount of cost for hospitals.
Example two
Fig. 2 is a flowchart of a method for assisting a decision of ventilator-associated pneumonia according to a second embodiment of the present invention, which is further optimized based on the above embodiments. As shown in fig. 2, the method includes:
s210, determining a candidate webpage related to the ventilator-associated pneumonia through the keywords.
In this embodiment, the generation of the diagnostic treatment model is embodied. First, candidate web pages related to ventilator-associated pneumonia are captured from the Internet through keywords. Optionally, the candidate web page includes a document related to the ventilator-associated pneumonia, and may also include a picture, a meeting report, and/or a news report related to the ventilator-associated pneumonia. Preferably, a web page including a document relating to ventilator-associated pneumonia is used as the candidate web page, and the information accuracy of the candidate web page is improved. The keywords comprise ventilator-associated pneumonia, diagnosis, treatment, and/or prevention, and the web pages matched with the keywords are used as candidate web pages.
S220, extracting the text information in each candidate webpage, matching the extracted text information with a preset key field, and judging whether each candidate webpage is a webpage related to the ventilator-associated pneumonia.
To ensure the accuracy of the web page information, key fields related to ventilator-associated pneumonia may be preset. After the candidate webpage is obtained, extracting text information in the candidate webpage through a semantic analysis technology, and matching the extracted text information of the candidate webpage with the key field. For example, when a document related to ventilator-associated pneumonia is included in the candidate webpage, text information in the document is extracted, and the extracted text information is matched with a preset key field. If the matching is successful, judging that the candidate webpage to which the text information belongs is a related webpage related to the ventilator-associated pneumonia; otherwise, judging that the candidate webpage to which the text message belongs is not a related webpage related to the ventilator-associated pneumonia. The candidate webpages are screened by setting the key fields, so that the accuracy of the corpus used for training the diagnosis and treatment model can be ensured, and the auxiliary diagnosis information of the diagnosis and treatment model is more accurate.
And S230, performing text analysis on the text information of the related webpage to construct a diagnosis and treatment model.
Optionally, the screened text information of the related webpage related to the ventilator-associated pneumonia is analyzed, information such as diagnosis basis, infection risk factors, and/or treatment means of the ventilator-associated pneumonia in the text information is extracted, and the information is structured to generate a corresponding diagnosis and treatment rule so as to generate a diagnosis and treatment model.
In this embodiment, the corpus may be trained using a machine learning algorithm. For example, the features in the text information can be marked manually, the features are used as training samples to train the diagnosis and treatment model to obtain a trained diagnosis and treatment model, then part of the patient information data is used for verifying the trained diagnosis and treatment model, and the verified diagnosis and treatment model is used as a final diagnosis and treatment model, so that the accuracy of the auxiliary diagnosis information is further improved.
Optionally, the diagnostic therapy model includes at least one of a diagnostic sub-model, a prophylactic sub-model, and a therapeutic sub-model. In this embodiment, the classifier may be used to extract and classify the text information of the related web pages, divide the corpus into a diagnosis corpus, a prevention corpus and a treatment corpus, and then train the corresponding corpus respectively to generate the corresponding sub-models.
For example, when the extracted text information of the relevant web page is: "clinical diagnosis of ventilator-associated pneumonia is based on one of the following conditions: a. blood cells >10.0 × 109/L or <4 × 109/L with or without nuclear transfer; b. fever, body temperature >37.5 ℃, large amount of purulent secretion in respiratory tract; c. when new pathogenic bacteria are separated from bronchial secretions after onset of disease, the text information is marked as diagnosis linguistic data through a classifier. And extracting the characteristic text in the text information, and determining the corresponding data range. And extracting the diagnosis rules in the text information, and training the diagnosis rules together with the diagnosis rules extracted from other related webpages to generate a diagnosis submodel.
And S240, receiving patient sign data sent by the physical sign monitoring equipment.
And S250, acquiring patient inspection data through a hospital management system.
And S260, generating auxiliary diagnosis information according to the patient sign data, the patient inspection data and a diagnosis and treatment model obtained through pre-training, wherein the diagnosis and treatment model is obtained through corpus training of ventilator-associated pneumonia.
The technical scheme of the embodiment of the invention embodies the generation process of the diagnosis and treatment model on the basis of the embodiment. By using the method, the accuracy of the linguistic data used for generating the diagnosis and treatment model is ensured, so that the diagnosis and treatment model is more accurate, and the accuracy of auxiliary diagnosis information output by the diagnosis and treatment model is improved.
EXAMPLE III
Fig. 3 is a flowchart of a method for assisting a decision of ventilator-associated pneumonia according to a third embodiment of the present invention, and the present embodiment is further optimized based on the above embodiments. As shown in fig. 3, the method includes:
and S310, receiving patient sign data sent by the physical sign monitoring equipment.
And S320, acquiring patient inspection data through a hospital management system.
S330, inputting the patient sign data and the patient inspection data into a diagnosis submodel in the diagnosis and treatment model.
After the physical sign data and the patient inspection data of the patient are acquired, the physical sign data and the patient inspection data of the patient are input into a diagnosis and treatment model, the diagnosis and treatment model inputs all input data into a diagnosis sub-model for diagnosis according to a preset analysis process, the diagnosis sub-model analyzes according to the input data, and a diagnosis result is output.
And S340, obtaining a diagnosis result output by the diagnosis submodel.
In this embodiment, the diagnosis result output by the diagnosis submodel is infected or not infected, and the subsequent analysis operation is judged according to the diagnosis result output by the diagnosis submodel. Alternatively, when a patient is infected, a more specific diagnosis may be output, such as a mild infection, a moderate infection, or a severe infection.
And S350, inputting the patient sign data, the patient test data and the diagnosis result into a sub-model matched with the diagnosis result according to the diagnosis result.
Optionally, when the patient is judged to be not infected according to the diagnosis result, the patient sign data, the patient examination data and the diagnosis result are input into a preset prevention sub-model.
And when the diagnosis result is that the patient does not have the ventilator-associated pneumonia, inputting the physical sign data of the patient, the patient inspection data and the non-infection result into the prevention sub-model, and analyzing the prevention sub-model according to the input data and outputting corresponding auxiliary prevention information.
Optionally, when the infection of the patient is judged according to the diagnosis result, the patient sign data, the patient examination data and the diagnosis result are input into a preset treatment sub-model.
And when the diagnosis result is that the patient has infected the ventilator-associated pneumonia, inputting the physical sign data of the patient, the patient inspection data and the infection result into a diagnosis sub-model, and analyzing the diagnosis sub-model according to the input data and outputting corresponding auxiliary diagnosis information.
And S360, acquiring auxiliary diagnosis information output by the submodel matched with the diagnosis result.
In the embodiment, when the diagnosis result is that the patient is not infected, the auxiliary prevention information output by the prevention sub-model is acquired; and when the diagnosis result is the infection of the patient, acquiring the auxiliary treatment information output by the treatment sub-model. Optionally, the auxiliary prevention information is a feasible preventive measure for assisting medical staff to perform ventilator-associated pneumonia prevention according to the current patient condition, and the auxiliary treatment information is a feasible treatment scheme for assisting medical staff to perform ventilator-associated pneumonia treatment according to the current patient condition.
Optionally, when the diagnosis result is that the patient is not infected, the prevention sub-model outputs auxiliary prevention information to assist medical staff in preventing the ventilator-associated pneumonia. For example, the auxiliary preventive information can be classified into preventive measures related to instruments, preventive measures related to operations, preventive measures for drugs, and clustering schemes. Optionally, the apparatus-related precautions include: the heat-humidity exchanger is replaced, the sputum suction device is replaced regularly, and the like; operational related precautions include: tracheal intubation route, subglottal secretion drainage, exogenous infection control, and the like; the drug preventive measures include: aerosol inhalation of antibacterial drugs, intravenous administration of antibacterial drugs, etc.; the bundling scheme comprises the following steps: lifting the bed head, nursing the oral cavity, removing condensed water in the pipeline of the breathing machine, turning over and the like. Specifically, the specific information list of various preventive measures can be displayed for the reference of medical staff.
Optionally, when the diagnosis result is that the patient is infected, the treatment sub-model outputs auxiliary treatment information to assist medical staff in treating the ventilator-associated pneumonia. Specifically, the treatment sub-model can determine the infection degree of the patient by combining the diagnosis result output by the diagnosis sub-model, and then generate a corresponding treatment scheme according to the physical sign data of the patient and the inspection data of the patient, and the treatment scheme is output as auxiliary treatment information to be referred to medical staff. The treatment scheme can comprise ventilator-associated pneumonia antibacterial drug treatment, glucocorticoid application, physical therapy application and the like.
It should be noted that, the preventive sub-model and the diagnostic sub-model can output corresponding auxiliary treatment information and auxiliary diagnostic information, and can display the analysis results of each physical sign data and each inspection data of the patient to the medical staff, so as to assist the medical staff to perform corresponding prevention and treatment.
The technical scheme of the embodiment of the invention embodies the process of outputting the auxiliary diagnosis information through the diagnosis and treatment model on the basis of the embodiment. By using the method, the next auxiliary prevention analysis or auxiliary treatment analysis can be carried out according to the diagnosis result of the diagnosis sub-model, and the corresponding auxiliary prevention information or auxiliary treatment information is output, so that the auxiliary diagnosis information is more accurate, and more effective prevention and treatment suggestions are provided for medical staff.
On the basis of the above scheme, after the auxiliary prevention information output by the prevention submodel is acquired, the method further includes:
and sending the operation to be executed by each medical device contained in the auxiliary prevention information to the corresponding medical device.
In this embodiment, intelligent reminding of preventive measures can also be achieved. Specifically, each medical device and the operation to be executed by the medical device included in the auxiliary prevention information can be extracted, corresponding reminding information is generated, and then the reminding information is sent to the corresponding medical device in a wireless communication mode to remind medical staff of executing the corresponding operation, so that intelligent reminding of preventive measures is realized.
Example four
Fig. 4 is a schematic structural diagram of a ventilator-associated pneumonia decision support apparatus according to a fourth embodiment of the present invention. The apparatus for assisting in determining pneumonia related to a breathing machine can be implemented in software and/or hardware, for example, the apparatus for assisting in determining pneumonia related to a breathing machine can be configured in a breathing machine related pneumonia determination assisting device, as shown in fig. 4, and the apparatus includes:
a sign data acquisition module 410, configured to receive patient sign data sent by the sign monitoring device;
a test data acquisition module 420 for acquiring patient test data via a hospital management system;
the diagnosis information generating module 430 is configured to generate auxiliary diagnosis information according to the patient sign data, the patient examination data, and a diagnosis and treatment model obtained through pre-training, where the diagnosis and treatment model is obtained through training according to the corpus of the ventilator-associated pneumonia.
Further, the apparatus further comprises:
a model construction module for constructing the diagnostic treatment model;
the model building module further comprises:
the candidate webpage determining unit is used for determining a candidate webpage related to the ventilator-associated pneumonia through the keywords;
the relevant webpage extracting unit is used for extracting the text information in each candidate webpage, matching the extracted text information with a preset key field and judging whether each candidate webpage is a relevant webpage related to the ventilator-associated pneumonia;
and the model building unit is used for performing text analysis on the text information of the related webpage and building a diagnosis and treatment model.
Further, the diagnostic information generating module 430 includes:
a data input unit for inputting the patient sign data and the patient test data into a diagnostic submodel in the diagnostic therapy model;
a result obtaining unit for obtaining a diagnosis result output by the diagnosis submodel;
the result matching unit is used for inputting the patient sign data, the patient test data and the diagnosis result into a sub-model matched with the diagnosis result according to the diagnosis result;
and the information acquisition unit is used for acquiring auxiliary diagnosis information output by the submodel matched with the diagnosis result.
Further, the result matching unit is specifically configured to:
when the patient is judged to be not infected according to the diagnosis result, inputting the patient sign data, the patient inspection data and the diagnosis result into a preset prevention sub-model;
the information acquisition unit is specifically configured to:
and acquiring auxiliary prevention information output by the prevention submodel.
Further, the result matching unit is specifically configured to:
when the infection of the patient is judged according to the diagnosis result, the patient sign data, the patient inspection data and the diagnosis result are input into a preset treatment sub-model;
the information acquisition unit is specifically configured to:
and acquiring auxiliary treatment information output by the treatment sub-model.
Further, the apparatus further comprises:
and the command sending module is used for sending the operation to be executed by each medical device contained in the auxiliary prevention information to the corresponding medical device after the auxiliary prevention information output by the prevention sub-model is acquired.
According to the embodiment of the invention, the patient sign data sent by the sign monitoring equipment is received through the sign data acquisition module; the inspection data acquisition module acquires patient inspection data through a hospital management system; the diagnosis information generation module generates auxiliary diagnosis information according to the patient sign data, the patient inspection data and a diagnosis and treatment model obtained by pre-training according to the corpus of the ventilator-associated pneumonia, provides auxiliary decision-making information of 'from pre-treatment to treatment' of the ventilator-associated pneumonia for clinical medical staff, timely and effectively diagnoses and treats the ventilator-associated pneumonia of the patient, and improves the diagnosis efficiency of the ventilator-associated pneumonia.
The breathing machine-related pneumonia decision auxiliary device provided by the embodiment of the invention can execute the breathing machine-related pneumonia decision auxiliary method provided by any embodiment of the invention, and has corresponding functional modules and beneficial effects of the execution method.
EXAMPLE five
Fig. 5 is a schematic structural diagram of an auxiliary apparatus for determining ventilator-associated pneumonia according to a fifth embodiment of the present invention. Fig. 5 illustrates a block diagram of an exemplary ventilator-associated pneumonia decision aid 512 suitable for use in implementing embodiments of the present invention. The ventilator-associated pneumonia decision aid 512 shown in fig. 5 is only an example and should not impose any limitations on the functionality and scope of use of embodiments of the present invention.
As shown in fig. 5, the ventilator-associated pneumonia decision aid 512 is in the form of a general purpose computing device. Components of the ventilator-associated pneumonia decision aid 512 may include, but are not limited to: one or more processing units 516, a system memory 528, and a bus 518 that couples various system components including the system memory 528 and the processing units 516.
The ventilator-associated pneumonia decision aid 512 typically includes a variety of computer system readable media. These media may be any available media that can be accessed by the ventilator associated pneumonia decision aid 512 and includes both volatile and nonvolatile media, removable and non-removable media.
The system memory 528 may include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM)530 and/or cache memory 532. The ventilator-associated pneumonia decision aid 512 may further include other removable/non-removable, volatile/non-volatile computer system storage media. By way of example only, storage 534 may be used to read from and write to non-removable, nonvolatile magnetic media (not shown in FIG. 5, and commonly referred to as a "hard drive"). Although not shown in FIG. 5, a magnetic disk drive for reading from and writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 518 through one or more data media interfaces. Memory 528 may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the invention.
A program/utility 540 having a set (at least one) of program modules 542, including but not limited to an operating system, one or more application programs, other program modules, and program data, may be stored in, for example, the memory 528, each of which examples or some combination may include an implementation of a network environment. The program modules 542 generally perform the functions and/or methods of the described embodiments of the invention.
The ventilator-associated pneumonia decision aid 512 may also communicate with one or more external devices 514 (e.g., keyboard, pointing device, display 524, etc.), with one or more devices that enable a user to interact with the ventilator-associated pneumonia decision aid 512, and/or with any device (e.g., network card, modem, etc.) that enables the ventilator-associated pneumonia decision aid 512 to communicate with one or more other computing devices. Such communication may occur via input/output (I/O) interfaces 522. Also, the ventilator associated pneumonia decision aid 512 may also communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network, such as the internet) via the network adapter 520. As shown, the network adapter 520 communicates with the other modules of the ventilator associated pneumonia decision aid 512 via a bus 518. It should be appreciated that, although not shown in the figures, other hardware and/or software modules may be used in conjunction with the ventilator-associated pneumonia decision aid 512, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.
The processing unit 516 executes programs stored in the system memory 528 to execute various functional applications and data processing, for example, to implement the method for assisting the decision of ventilator-related pneumonia according to the embodiment of the present invention, the method includes:
receiving patient sign data sent by sign monitoring equipment;
acquiring patient inspection data through a hospital management system;
and generating auxiliary diagnosis information according to the patient sign data, the patient inspection data and a diagnosis and treatment model obtained by pre-training, wherein the diagnosis and treatment model is obtained by training according to the corpus of the ventilator-associated pneumonia. Of course, those skilled in the art will understand that the processing unit may also implement the technical solution of the ventilator-associated pneumonia decision assistance method provided by any embodiment of the present invention.
EXAMPLE six
An embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements a method for assisting a decision making of ventilator-associated pneumonia according to an embodiment of the present invention, where the method includes:
receiving patient sign data sent by sign monitoring equipment;
acquiring patient inspection data through a hospital management system;
and generating auxiliary diagnosis information according to the patient sign data, the patient inspection data and a diagnosis and treatment model obtained by pre-training, wherein the diagnosis and treatment model is obtained by training according to the corpus of the ventilator-associated pneumonia.
Of course, the computer-readable storage medium provided by the embodiments of the present invention, on which the computer program is stored, is not limited to the method operations described above, and may also perform related operations in the ventilator-associated pneumonia decision assistance method provided by any embodiment of the present invention.
Computer storage media for embodiments of the invention may employ any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims (8)
1. A method for assisting in decision making of ventilator-associated pneumonia, comprising:
receiving patient sign data sent by sign monitoring equipment;
acquiring patient inspection data through a hospital management system;
generating auxiliary diagnosis information according to patient sign data, patient inspection data and a diagnosis and treatment model obtained by pre-training, wherein the diagnosis and treatment model is obtained by training according to the corpus of the ventilator-associated pneumonia;
wherein, the generating of the auxiliary diagnosis information according to the patient sign data, the patient inspection data and the diagnosis and treatment model obtained by pre-training comprises:
inputting the patient vital sign data and the patient test data into a diagnostic submodel in the diagnostic therapy model;
obtaining a diagnosis result output by the diagnosis submodel;
inputting the patient sign data, the patient test data and the diagnosis result into a sub-model matched with the diagnosis result according to the diagnosis result;
acquiring auxiliary diagnosis information output by the submodel matched with the diagnosis result;
the construction of the diagnosis and treatment model comprises the following steps:
determining candidate web pages related to the ventilator-associated pneumonia through the keywords;
extracting text information in each candidate webpage, matching the extracted text information with a preset key field, and judging whether each candidate webpage is a related webpage related to ventilator-associated pneumonia;
and performing text analysis on the text information of the related webpage to construct a diagnosis and treatment model.
2. The method of claim 1, wherein said entering said patient vital data, said patient test data, and said diagnostic result into a sub-model matching said diagnostic result as a function of said diagnostic result comprises:
when the patient is judged to be not infected according to the diagnosis result, inputting the patient sign data, the patient inspection data and the diagnosis result into a preset prevention sub-model;
the step of acquiring auxiliary diagnosis information output by the submodel matched with the diagnosis result comprises the following steps:
and acquiring auxiliary prevention information output by the prevention submodel.
3. The method of claim 1, wherein said entering said patient vital data, said patient test data, and said diagnostic result into a sub-model matching said diagnostic result as a function of said diagnostic result comprises:
when the infection of the patient is judged according to the diagnosis result, the patient sign data, the patient inspection data and the diagnosis result are input into a preset treatment sub-model;
the step of acquiring auxiliary diagnosis information output by the submodel matched with the diagnosis result comprises the following steps:
and acquiring auxiliary treatment information output by the treatment sub-model.
4. The method of claim 2, further comprising, after obtaining the auxiliary preventive information output by the preventive submodel:
and sending the operation to be executed by each medical device contained in the auxiliary prevention information to the corresponding medical device.
5. A ventilator-associated pneumonia decision assistance apparatus, comprising:
the physical sign data acquisition module is used for receiving the physical sign data of the patient sent by the physical sign monitoring equipment;
the examination data acquisition module is used for acquiring patient examination data through a hospital management system;
the diagnosis information generation module is used for generating auxiliary diagnosis information according to the patient sign data, the patient inspection data and a diagnosis and treatment model obtained through pre-training, wherein the diagnosis and treatment model is obtained through corpus training of ventilator-associated pneumonia;
wherein the diagnostic information generation module comprises:
a data input unit for inputting the patient sign data and the patient test data into a diagnostic submodel in the diagnostic therapy model;
a result obtaining unit for obtaining a diagnosis result output by the diagnosis submodel;
the result matching unit is used for inputting the patient sign data, the patient test data and the diagnosis result into a sub-model matched with the diagnosis result according to the diagnosis result;
the information acquisition unit is used for acquiring auxiliary diagnosis information output by the submodel matched with the diagnosis result;
the construction of the diagnosis and treatment model comprises the following steps:
determining candidate web pages related to the ventilator-associated pneumonia through the keywords;
extracting text information in each candidate webpage, matching the extracted text information with a preset key field, and judging whether each candidate webpage is a related webpage related to ventilator-associated pneumonia;
and performing text analysis on the text information of the related webpage to construct a diagnosis and treatment model.
6. The apparatus of claim 5, further comprising:
a model construction module for constructing the diagnostic treatment model;
the model building module further comprises:
the candidate webpage determining unit is used for determining a candidate webpage related to the ventilator-associated pneumonia through the keywords;
the relevant webpage extracting unit is used for extracting the text information in each candidate webpage, matching the extracted text information with a preset key field and judging whether each candidate webpage is a relevant webpage related to the ventilator-associated pneumonia;
and the model building unit is used for performing text analysis on the text information of the related webpage and building a diagnosis and treatment model.
7. A ventilator-associated pneumonia decision aid, the device comprising:
one or more processors;
storage means for storing one or more programs;
when executed by the one or more processors, cause the one or more processors to implement the ventilator-associated pneumonia decision assistance method of any one of claims 1-4.
8. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out a method for assisting in the decision of ventilator-associated pneumonia according to any one of claims 1 to 4.
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| CN111383754B (en) * | 2018-12-28 | 2023-08-08 | 医渡云（北京）技术有限公司 | Medical decision method, medical decision device, electronic device, and storage medium |
| CN109785961A (en) * | 2018-12-29 | 2019-05-21 | 上海依智医疗技术有限公司 | A kind of equipment differentiating asthma |
| CN109785960A (en) * | 2018-12-29 | 2019-05-21 | 上海依智医疗技术有限公司 | A kind of method and device differentiating asthma |
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| CN110517767B (en) * | 2019-08-27 | 2022-12-13 | 北京百度网讯科技有限公司 | Auxiliary diagnosis method, auxiliary diagnosis device, electronic equipment and storage medium |
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