CN114842935B - Intelligent detection method and system for night ward round of hospital - Google Patents
Intelligent detection method and system for night ward round of hospital Download PDFInfo
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
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- G06K17/0022—Methods or arrangements for effecting co-operative working between equipments covered by two or more of main groups G06K1/00 - G06K15/00, e.g. automatic card files incorporating conveying and reading operations arrangements or provisious for transferring data to distant stations, e.g. from a sensing device
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- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/70—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
Abstract
The invention provides an intelligent detection method and system for night ward rounds of hospitals, and relates to the technical field of artificial intelligence, wherein the method comprises the following steps: constructing an early warning scheme according to basic information of a patient; the method comprises the steps of detecting vital signs of a patient in real time by using an intelligent wristband to obtain real-time sign information; generating abnormal early warning according to the real-time physical sign information of the patient and the early warning scheme; traversing the history records based on the abnormal early warning to obtain an optimal history reference medical record; and extracting the detection record of the optimal historical reference medical records, and performing night ward inspection detection on the patient. The technical problems that abnormal signs of a patient cannot be found in time during night ward round in the prior art, and whether the body of the patient is abnormal or not cannot be accurately judged are solved. The abnormal state of the patient is monitored and early-warned in real time through a computer technology, and a reference is provided for the pertinence of the night ward round of medical staff, so that the night ward round quality and effect are improved, and the technical effect of the life safety of the patient is better ensured.
Description
Technical Field
The invention relates to the technical field of artificial intelligence, in particular to an intelligent detection method and system for night ward rounds of hospitals.
Background
Ward round is an important means for ensuring effective operation of medical safety quality system in clinical departments in hospitals. The hospital safety is weak at night, the number of the hospital stay people of clinicians and nurses is less than that of the hospital stay people in the daytime, and in order to avoid the occurrence of medical accidents that sudden physical sign abnormality occurs but people are not helped at night when medical resources of patients to be treated are weak, modern medicine establishes the standard and specification of night ward-round.
At present, for the night ward-round of a light patient, generally, the body temperature and heart rate and other sign information of a target patient are acquired at regular time by nurses or doctors, and when the sign information of the patient is abnormal, the patient is rescued by means of clinical experience of medical staff. At present, part of hospitals also acquire the sign information of each patient through weak intelligent equipment so as to reduce the workload of medical staff in the aspect of patient sign information acquisition.
Due to the complexity of disease types and the diversity of pathological manifestations of patients, medical staff in the prior art cannot find abnormal signs of the patients in time when making night rounds, and further cannot accurately judge whether the bodies of the patients are abnormal, so that the technical problems of low quality and poor effect of night rounds are caused.
Disclosure of Invention
The application provides an intelligent detection method and system for night ward round of a hospital, which are used for solving the technical problems that medical staff in the prior art cannot find abnormal signs of a patient in time when checking a round at night, and further cannot accurately judge whether the body of the patient is abnormal, so that the night ward round quality is low and the effect is poor.
In view of the above problems, the application provides an intelligent detection method and system for night ward rounds of hospitals.
In a first aspect of the present application, there is provided an intelligent detection method for night ward rounds of hospitals, the method comprising: collecting first basic information of a first patient, and constructing a first early warning scheme according to the first basic information; performing format conversion on the first basic information to obtain a first dynamic two-dimensional code; performing vital sign real-time detection on the first patient by using a smart wristband to obtain first real-time vital sign information; according to the first real-time physical sign information, updating the first dynamic two-dimensional code in real time; scanning and analyzing the first dynamic two-dimensional code, and generating a first abnormal early warning according to the first early warning scheme; traversing the history medical records based on the first abnormal early warning to obtain a first history reference medical record; and extracting a first history detection record of the first history reference medical record, and performing night ward inspection on the first patient based on the first history detection record.
In a second aspect of the present application, there is provided an intelligent detection system for a hospital nocturnal ward, the system comprising: the first construction unit is used for collecting first basic information of a first patient and constructing a first early warning scheme according to the first basic information; the first obtaining unit is used for carrying out format conversion on the first basic information to obtain a first dynamic two-dimensional code; the second obtaining unit is used for detecting vital signs of the first patient in real time by utilizing the intelligent wristband to obtain first real-time sign information; the first execution unit is used for updating the first dynamic two-dimensional code in real time according to the first real-time physical sign information; the first generation unit is used for scanning and analyzing the first dynamic two-dimensional code and generating a first abnormal early warning according to the first early warning scheme; the third obtaining unit is used for traversing the history medical records based on the first abnormal early warning to obtain a first history reference medical record; and the first detection unit is used for extracting a first history detection record of the first history reference medical record and carrying out night ward inspection on the first patient based on the first history detection record.
In a third aspect of the present application, there is provided an intelligent detection device for night ward rounds of hospitals, comprising: a processor coupled to a memory for storing a program which, when executed by the processor, causes the system to perform the steps of the method as described in the first aspect.
In a fourth aspect of the present application, there is provided a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the method according to the first aspect.
One or more technical solutions provided in the present application have at least the following technical effects or advantages:
the method provided by the embodiment of the application comprises the steps of collecting first basic information of a first patient, and constructing a first early warning scheme according to the first basic information; performing format conversion on the first basic information to obtain a first dynamic two-dimensional code; performing vital sign real-time detection on the first patient by using the intelligent wristband to obtain first real-time vital sign information; according to the first real-time physical sign information, updating the first dynamic two-dimensional code in real time; scanning and analyzing the first dynamic two-dimensional code, and generating a first abnormal early warning according to the first early warning scheme; traversing the history medical records based on the first abnormal early warning to obtain a first history reference medical record; and extracting a first history detection record of the first history reference medical record, and performing night ward inspection on the first patient based on the first history detection record. According to the method and the device, the first basic information of the first patient is collected, the first early warning scheme is built according to the first basic information, and the situation that the abnormal sign of the patient is misjudged to be the abnormal sign of the patient due to the fact that the normal sign of the patient is higher than the sign value of the healthy person in a certain diseased state is avoided. Performing format conversion on the first basic information to obtain a first dynamic two-dimensional code; utilize the intelligent wrist strap is right carry out vital sign real-time detection to first patient, obtain first real-time sign information, according to first real-time sign information, to carry out real-time update to first dynamic two-dimensional code, accomplish the real-time acquisition and the real-time update to patient vital sign through the intelligent wrist strap, reduced medical personnel's work load in the aspect of patient vital sign index collection, reduced medical personnel's physical stamina consumption. Scanning and analyzing the first dynamic two-dimensional code, and generating a first abnormal early warning according to the first early warning scheme; traversing the history medical records based on the first abnormal early warning to obtain a first history reference medical record; and extracting a first history detection record of the first history reference medical record, and performing night ward inspection on the first patient based on the first history detection record. Through computer technology real-time supervision and early warning patient's unusual, reached the medical personnel that makes rounds at night can in time accurately learn patient's unusual physical sign, provide the reference for medical personnel's the pertinence of making rounds at night, reached improvement quality and the effect of making rounds at night to guarantee patient's life safety's technical effect better.
The foregoing description is only an overview of the technical solutions of the present application, and may be implemented according to the content of the specification in order to make the technical means of the present application more clearly understood, and in order to make the above-mentioned and other objects, features and advantages of the present application more clearly understood, the following detailed description of the present application will be given.
Drawings
Fig. 1 is a schematic flow chart of an intelligent detection method for night ward rounds of a hospital provided by the application;
fig. 2 is a schematic flow chart of constructing a first early warning scheme according to first basic information in the intelligent detection method for night ward rounds of hospitals provided by the application;
fig. 3 is another flow chart of constructing a first early warning scheme in the intelligent detection method for night ward rounds of hospitals provided by the application;
FIG. 4 is a schematic diagram of an intelligent detection system for night ward rounds in a hospital;
fig. 5 is a schematic structural diagram of an exemplary electronic device of the present application.
Reference numerals illustrate: the device comprises a first construction unit 11, a first obtaining unit 12, a second obtaining unit 13, a first executing unit 14, a first generating unit 15, a third obtaining unit 16, a first detection unit 17, an electronic device 300, a memory 301, a processor 302, a communication interface 303, and a bus architecture 304.
Detailed Description
The application provides an intelligent detection method and system for night ward round of a hospital, which are used for solving the technical problems that medical staff in the prior art cannot find abnormal signs of a patient in time when checking a round at night, and further cannot accurately judge whether the body of the patient is abnormal, so that the night ward round quality is low and the effect is poor.
Summary of the application
Night ward-round is a hospital management measure for ensuring that even if sudden abnormal vital signs appear at night with weaker medical resources for patients admitted to hospital, the abnormal vital signs can be found and treated in time, and is an important means for avoiding the vital health of the patients from being endangered. However, the existing night ward round for collecting vital signs of patients and treating patients with abnormal vital signs are highly dependent on medical staff. In the prior art, when medical staff performs night ward rounds, abnormal signs of a patient cannot be found in time, and whether the body of the patient is abnormal or not cannot be accurately judged, so that the technical problems of low night ward rounds quality and poor effect are caused.
Aiming at the technical problems, the technical scheme provided by the application has the following overall thought:
the method comprises the steps of collecting first basic information of a first patient, and constructing a first early warning scheme according to the first basic information; performing format conversion on the first basic information to obtain a first dynamic two-dimensional code; performing vital sign real-time detection on the first patient by using the intelligent wristband to obtain first real-time vital sign information; according to the first real-time physical sign information, updating the first dynamic two-dimensional code in real time; scanning and analyzing the first dynamic two-dimensional code, and generating a first abnormal early warning according to the first early warning scheme; traversing the history medical records based on the first abnormal early warning to obtain a first history reference medical record; and extracting a first history detection record of the first history reference medical record, and performing night ward inspection on the first patient based on the first history detection record. The medical staff for night ward round can timely and accurately learn the abnormal signs of the patient, and rapidly make a detection scheme to diagnose and treat the patient, so that the life safety of the patient is guaranteed. Having introduced the basic principles of the present application, the technical solutions herein will now be clearly and fully described with reference to the accompanying drawings, it being apparent that the described embodiments are only some of the embodiments of the present application, and not all of the embodiments of the present application, and it is to be understood that the present application is not limited by the example embodiments described herein. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments of the present application without making any inventive effort, are intended to be within the scope of the present application. It should be further noted that, for convenience of description, only some, but not all of the drawings related to the present application are shown.
Example 1
As shown in fig. 1, the present application provides an intelligent detection method for night ward rounds of a hospital, the method being applied to an intelligent detection system for night ward rounds of a hospital, the system being in communication connection with a smart wristband, the method comprising:
s100: collecting first basic information of a first patient, and constructing a first early warning scheme according to the first basic information;
specifically, the first patient is a patient currently admitted to treatment and is in clinical view. The first basic information is patient information including basic physical condition, diagnosis, sex, surgery, treatment, past medical history, and the like of the first patient, which can be used for reference comparison to determine whether the first patient currently has vital sign abnormality, and current medical doctors and responsible nurses of the first patient. Optionally, when the patient is a patient who has just been admitted, the first basic information includes basic information such as sex, age, etc. of the patient, disease information such as physical condition, preliminary diagnosis, etc. and history information such as history disease record, history treatment information, etc., and when the patient is a patient who has undergone surgery or other treatment such as medication after admission, the first basic information includes treatment information of various modes such as surgery, medication, etc. that the patient has undergone after admission, in addition to the first basic information related information of the patient who has just been admitted. The first early warning scheme is a judging method for determining whether the first patient has abnormal signs currently and needs diagnosis and treatment.
Optionally, the first basic information of the first patient may be acquired through a hospital HIS system or a medical system intranet between hospital departments, and the first early warning scheme of the first patient may be determined through data analysis or based on clinical experience of medical staff based on the first basic information of the first patient.
S200: performing format conversion on the first basic information to obtain a first dynamic two-dimensional code;
specifically, it should be understood that the two-dimensional code is an open information memory, and data symbol information is recorded by distributing and adopting patterns with black and white intervals on the two-dimensional code according to an arrangement rule by using a specific geometric figure, and the stored data symbol information is read out based on a computer identifier. The information stored in the two-dimensional code pattern is conveniently identified by the computer identifier. When stored, it is necessary to convert human language information into a computer language, using the numbers "0" and "1" as codes, and simultaneously representing alphanumeric information using a number of geometric shapes corresponding to binary.
The format conversion is used for converting the acquired first basic information from a text format into a computer language consisting of a plurality of 0 and 1. The first dynamic two-dimensional code is a bedside board with a small display, wherein the bedside board is arranged on a patient bed of a specific patient, and the two-dimensional code image on the bedside board display can be generated based on the first basic information of different patients and generates corresponding change when the first basic information of the first patient changes.
In this embodiment, format conversion is performed on the first basic information of the first patient, and the first basic information is converted into a computer language format and forms a corresponding two-dimensional code, namely a first dynamic two-dimensional code; the headboard on the first patient bed displays the first dynamic two-dimensional code.
S300: performing vital sign real-time detection on the first patient by using the intelligent wristband to obtain first real-time vital sign information;
specifically, the intelligent wrist strap is intelligent wearing equipment with a heartbeat sensing device, a temperature sensing device and a positioning device, wherein the intelligent wearing equipment can intelligently detect part of vital signs of a patient, and can acquire part of vital signs of a wearer in real time. The first real-time vital sign information is a partial vital sign of the first patient obtained through the smart wristband detection. In this embodiment, the smart wristband detects a part of vital signs of the first patient in real time, and temporarily records the vital signs of the first patient.
S400: according to the first real-time physical sign information, updating the first dynamic two-dimensional code in real time;
specifically, the intelligent wristband is in communication connection with a headboard display displaying a first dynamic two-dimensional code, the intelligent wristband stores the first real-time physical sign information of the first patient detected in real time, and transmits the first real-time physical sign information to a processor of the headboard dynamic two-dimensional code display in a computer language form composed of 0 and 1, and the processor correspondingly modifies the first basic information of the first patient stored in the two-dimensional code based on the first real-time dynamic information, so that the first dynamic two-dimensional code is updated in real time.
S500: scanning and analyzing the first dynamic two-dimensional code, and generating a first abnormal early warning according to the first early warning scheme;
specifically, it should understand that the purpose that this application set up dynamic two-dimensional code head of a bed tablet display is when maintaining patient privacy, makes things convenient for medical personnel to learn the basic information and the real-time sign information of current sick bed patient fast when making rounds at night. The first dynamic two-dimensional code is updated in real time, that is, relevant information of the first patient is displayed in real time. For example, the relevant information of the patient operation is automatically updated to the patient information after the operation, and then the latest relevant information of the patient is displayed in real time through the dynamic two-dimensional code.
The first abnormal early warning is an alarm which is externally sent out when the real-time vital signs of the patient are not matched with the numerical values in the first early warning scheme, and specifically, the first abnormal early warning comprises text information content of the specific abnormal vital signs sent out by medical staff through the system and an alarm which is made at the head of the patient in an acousto-optic mode.
S600: traversing the history medical records based on the first abnormal early warning to obtain a first history reference medical record;
specifically, the historical medical records are reference medical records databases constructed by the diagnosis records of the patient who is diagnosed by the current year of the hospital where the first patient is located and the corresponding diagnosis and treatment schemes and diagnosis and treatment effects. Optionally, the database of the history records hides the privacy information of the specific patient.
The first historical reference medical records are diagnosis and treatment medical records of historical patients, wherein the information of disease occurrence sign states, ages, disease histories and the like in the historical medical records is closest to the information of abnormal sign states, ages, disease histories and the like of current patients.
In this embodiment, the first abnormality early warning is traversed from the history record database as a search instruction to obtain the first history reference medical record.
S700: and extracting a first history detection record of the first history reference medical record, and performing night ward inspection on the first patient based on the first history detection record.
Specifically, the first history reference medical records contain information such as a specific disease diagnosis scheme and a medical detection item which are reserved by a doctor who treats the patient at the time, so that a specific detection record of the current diagnosis can be obtained through the first history reference medical records. Based on the similarity of the current abnormal sign condition of the first patient and the historical patient, the current night shift doctor and nurse can refer to the first historical detection record of the historical patient to perform night ward round detection on the current first patient. By referring to the detection record of the history medical records and combining the medical experience of medical staff, the determination and execution efficiency of the diagnosis and treatment scheme for diagnosing and treating the first patient is improved, and the night life safety of the patient is maintained.
According to the method and the device, the first basic information of the first patient is collected, the first early warning scheme is built according to the first basic information, and the situation that the abnormal sign of the patient is misjudged to be the abnormal sign of the patient due to the fact that the normal sign of the patient is higher than the sign value of the healthy person in a certain diseased state is avoided. Performing format conversion on the first basic information to obtain a first dynamic two-dimensional code; utilize the intelligent wrist strap is right carry out vital sign real-time detection to first patient, obtain first real-time sign information, according to first real-time sign information, to carry out real-time update to first dynamic two-dimensional code, accomplish the real-time acquisition and the real-time update to patient vital sign through the intelligent wrist strap, reduced medical personnel's work load in the aspect of patient vital sign index collection, reduced medical personnel's physical stamina consumption. Scanning and analyzing the first dynamic two-dimensional code, and generating a first abnormal early warning according to the first early warning scheme; traversing the history medical records based on the first abnormal early warning to obtain a first history reference medical record; and extracting a first history detection record of the first history reference medical record, and performing night ward inspection on the first patient based on the first history detection record. The medical staff for night ward round can timely and accurately learn the abnormal signs of the patient, and rapidly make a detection scheme to diagnose and treat the patient, so that the life safety of the patient is guaranteed.
Further, as shown in fig. 2, the method step S100 provided in the present application further includes:
s110: obtaining a first underlying disease and a first treatment regimen based on the first underlying information;
s120: sequentially analyzing the influence conditions of the first basic disease and the first treatment scheme on the sign indexes of the patient, and respectively generating a first influence sign index set and a second influence sign index set;
s130: performing union operation on the first influence sign index set and the second influence sign index set to generate a preset influence sign index set, wherein the preset influence sign index set comprises a plurality of sign indexes of which the sign indexes of a patient change;
s140: sequentially analyzing reasonable variation ranges of all the physical sign indexes to obtain a plurality of abnormal threshold values;
s150: constructing a sign index-abnormal threshold list according to the plurality of sign indexes and the plurality of abnormal thresholds;
s160: and constructing the first early warning scheme according to the sign index-abnormal threshold list.
Specifically, based on the step S100, the first basic information includes basic physical conditions, diagnosis, sex, operation, treatment, past medical history, and the like of the first patient, which can be used for reference to compare whether the first patient has abnormal vital signs at present, and current medical doctors and nurses who are responsible for the first patient.
The first underlying disease is the current condition diagnosed by the first patient at the time of admission. The first treatment regimen is a preliminary treatment regimen and a subsequent treatment regimen given by a current tube bed physician of the first patient and an outpatient clinician of the admission diagnosis. The first treatment scheme refers to treatment schemes such as surgery, medicines and the like which are undergone by the first patient after admission, and is information updated automatically. It should be noted that if the first patient has just been admitted and has not been treated in connection with a treatment regimen, the effect of the first treatment regimen on the patient's real-time sign is not considered.
The first influence sign index set is a sign item which changes under the influence of diseases after the first patient suffers from the diseases. The second influencing sign index set is a sign item of specific changes of hormone, heart rate, body temperature and the like caused by taking medicine and transfusion after the first patient receives treatment. The preset influence sign index set is a set of all sign indexes of the first patient, which change in the whole course from the beginning of disease to the complete cure of the disease.
Obtaining the first basic disease and a first treatment scheme according to the first basic information, determining the influence condition of the first basic disease on the sign index of the patient based on medical knowledge analysis, and generating a first influence sign index set; determining an influence condition of the first treatment regimen on the patient sign index based on medical knowledge analysis, generating a second influence sign index set; and obtaining the preset influence sign index set by the first influence sign index set and the second influence sign index set.
Determining a reasonable variation range of each physical sign index of the preset influence physical sign index set for the first patient based on the physical condition and physical constitution analysis of the first patient, and reversely pushing to obtain a plurality of abnormal threshold values corresponding to each physical sign index based on the reasonable variation range of each physical sign index; constructing a sign index-abnormal threshold list according to the plurality of sign indexes and the plurality of abnormal thresholds; and constructing the first early warning scheme according to the sign index-abnormal threshold list. And carrying out physical sign real-time detection on the first patient based on the physical sign index-abnormal threshold list, and correspondingly triggering the first abnormal early warning when a certain physical sign index in a preset influence physical sign index set of the first patient falls into the abnormal threshold of the physical sign index, so that medical staff checking a ward at night can timely or specific abnormal reasons of vital signs of the patient can be caused in a text information and lamplight sound mode, and the rescue time is shortened.
The vital sign project that the whole process of the first patient from suffering from the disease to diagnosis and treatment is changed is determined through analysis, the normal range of fluctuation change of the vital sign project is determined, and the data range of abnormal fluctuation conditions is reversely pushed, so that the specific vital sign of the first patient can be accurately positioned and detected in time, and medical staff is notified to carry out previous treatment. And because the numerical range of normal fluctuation of the vital sign of the first patient is determined during illness and treatment, unnecessary waste of medical resources caused by misjudgment of the normal sign during illness as an emergency due to deviation from the vital sign data of a healthy person is avoided. The technical effects of saving medical resources and facilitating medical staff to timely acquire the specific conditions of abnormal signs of patients so as to implement rescue as soon as possible are achieved.
Further, as shown in fig. 3, the constructing the first early warning scheme according to the sign index-abnormal threshold list further includes:
s161: scanning the first dynamic two-dimensional code to obtain the first real-time sign information, wherein the first real-time sign information comprises information of a plurality of real-time sign indexes;
s162: sequentially analyzing the normal range of each of the plurality of real-time physical sign indexes based on big data to obtain a plurality of thresholds;
s163: constructing a sign index-threshold list according to the plurality of sign indexes and the plurality of thresholds;
s164: extracting real-time information of a first sign index according to the first real-time sign information;
s165: judging whether the first sign index belongs to the preset influence sign index set or not;
s166: if the first physical sign index belongs to the preset influence physical sign index set, a first abnormal threshold value is obtained according to the physical sign index-abnormal threshold value list, and the first abnormal threshold value is used as an early warning judgment standard of the first physical sign index;
s167: and constructing the first early warning scheme according to the early warning judgment standard.
Specifically, the first dynamic two-dimensional code can reflect first real-time physical sign information of a user, and the first real-time physical sign information covers multiple real-time physical sign index data. The first physical sign index is a specific physical sign index in the first real-time physical sign information. The first abnormal threshold is specific abnormal threshold data of the first physical sign indexes in the preset influence physical sign index set, and when the first physical sign indexes of the first patient detected in real time fall into the first abnormal threshold, the first patient is judged to be in a physical sign abnormal state.
In this embodiment, a medical staff scans the first dynamic two-dimensional code through a handheld mobile terminal, obtains information of a plurality of real-time physical sign indexes of the first patient, sequentially analyzes normal ranges of each physical sign index in the plurality of real-time physical sign indexes based on big data, obtains a plurality of thresholds, and constructs a physical sign index-threshold list according to the plurality of physical sign indexes and the plurality of thresholds.
If the first physical sign index belongs to the preset influence physical sign index set, a first abnormal threshold value is obtained according to the physical sign index-abnormal threshold value list, and the first abnormal threshold value is used as an early warning judgment standard of the first physical sign index; and constructing the first early warning scheme according to the early warning judgment standard.
For example, based on the first early warning scheme, when the first sign index data falls within the first abnormal threshold, it is indicated that the sign index of the first patient is abnormal, and the system sends a first early warning scheme based on the abnormality to prompt the medical staff that the vital sign of the patient is abnormal and that the vital sign abnormality items are specifically present, so that the medical staff needs to be treated.
By constructing a first early warning scheme and taking whether the vital sign of the patient detected in real time falls into an abnormal threshold value as an early warning judgment standard, the technical effect of accurately positioning the vital abnormal sign of the first patient specifically appearing based on the standard, and timely and accurately informing the medical staff on duty at night of the abnormal vital sign of the first patient to implement rescue is achieved.
Further, the determining whether the first sign indicator belongs to the preset influence sign indicator set, and the method provided in the application step S165 further includes:
s165-1: if the first physical sign index does not belong to the preset influence physical sign index set, a first threshold value is obtained according to the physical sign index-threshold value list;
s165-2: and replacing the first abnormal threshold by the first threshold, namely taking the first threshold as the early warning judgment standard of the first sign index.
In particular, it should be understood that not all vital signs detected by the smart wristband are currently changing vital signs of the first patient due to the illness and disease treatment.
But vital signs of the part not affected by the first patient's illness can also reflect patient's physical condition information. And if the first physical sign index does not belong to the preset influence physical sign index set, obtaining a first threshold according to the physical sign index-threshold list, wherein the first threshold is specific threshold data of the first physical sign index which does not belong to the preset influence physical sign index set when the physical sign of the first patient is normal, and judging that the first patient is in a physical sign abnormal state when the first physical sign index of the first patient detected in real time does not fall into the first threshold. And replacing the first abnormal threshold by the first threshold, and taking the first threshold as the early warning judgment standard of the first sign index.
For example, a patient in which a bone injury is hospitalized usually has a body temperature which is not affected by treatment and fluctuates during clinical rest, but bedsores inflamed by long-term bedridden patients can cause fever, so that the temperature sign indexes which do not belong to a preset influence sign index set of the bone injury disease are obtained according to the sign index-threshold list, the change threshold of the temperature sign is used as the early warning judgment standard of the first sign index.
By bringing the sign change caused by the non-disease into the abnormal sign monitoring range, the method achieves the technical effects of comprehensively and accurately determining the vital abnormal signs of the first patient, and facilitating medical staff to timely know the accurate condition of the abnormal signs of the patient so as to implement rescue and avoid the damage to the vital safety of the patient at night.
Further, the step S600 of the method provided by the present application further includes:
s610: taking the real-time physical sign indexes, the first basic disease and the first treatment scheme as matching characteristic points to construct a characteristic point set, wherein the characteristic point set comprises a plurality of characteristic points;
s620: acquiring a historical medical record based on big data;
s630: traversing the history medical records according to the plurality of characteristic points to obtain a first history reference medical record.
Specifically, it should be understood that, when diagnosing a condition of a patient, a doctor determines the extent of the illness and the treatment plan of the patient mainly based on the sign information, the detection report, etc. of the patient at the time of the patient's visit, and constructs a medical record based on the above, which is archived and stored by a medical record management department, and a large number of medical records constitute the history medical record. Therefore, the complete historical records can be obtained according to the partial information search of the historical records.
In this embodiment, based on logic for obtaining a complete medical record according to the content of the medical record portion, the plurality of real-time physical sign indexes, the first basic disease, and the first treatment scheme are used as matching feature points, a feature point set including a plurality of feature points is constructed, and the historical medical record is traversed according to the plurality of feature points, so as to obtain a first historical reference medical record.
According to the embodiment, the information such as basic diseases and treatment schemes of the first patient are used as characteristic points, and the history records close to the current patient condition are obtained through big data and are used for consulting the current patient for diagnosis and treatment, so that the technical effects of consulting the abnormal condition of the patient by medical staff, and facilitating the medical staff to timely rescue the patient are achieved.
Further, the step S630 of the method provided in the present application further includes:
s631: performing importance level division on the plurality of feature points according to the importance degree to obtain a first division result;
s632: obtaining an importance level sign index according to the first division result;
S633: carrying out matching screening on the historical medical records according to the importance level sign indexes to obtain a candidate historical medical record set, wherein the candidate historical medical record set comprises a plurality of candidate historical medical records;
s634: and performing global optimization on the plurality of candidate historical medical records by utilizing tabu search to obtain the first historical reference medical record.
Specifically, for the multiple feature point importance levels obtained based on importance degree division, any one level is extracted, namely, the first division result obtains an importance level feature index, and the history records are subjected to matching screening based on the importance level feature index to obtain a candidate history record set.
By carrying out importance level division on the plurality of feature points, matching screening is carried out on the history records based on the importance level sign indexes, a basis is provided for obtaining candidate history records, and the reality, guidance and referenceability of finally obtained first history record information are improved.
The tabu search is a global-based meta heuristic random search algorithm. When optimizing a plurality of candidate historical medical records based on the tabu search algorithm, first determining an importance level sign index corresponding to a first division result, and further obtaining the plurality of candidate historical medical records. And then obtaining the historical case set of each importance level classification result based on a tabu search algorithm which does not specify a specific area. And similarly, obtaining the historical case sets corresponding to different grading results. By aiming at the characteristic indexes of different importance levels, the adaptive optimization of the historical medical records is respectively carried out in a targeted manner, so that the technical effect of obtaining the most preferable first historical reference medical records for medical staff to refer to for diagnosing, treating and detecting the first patient based on the current actual condition of the first patient is achieved.
Through optimizing based on global energy conveying parameters, the technical effects of tripping local optimization, improving rationality and referenceability of energy conveying parameter setting, further diagnosing and treating the first patient by a medical record treatment method with higher individuation degree, and improving the rescue efficiency of medical staff on the current patient are achieved.
Further, the method step S634 further includes performing global optimization on the plurality of candidate historical medical records by using tabu search to obtain the first historical reference medical record:
s634-1: extracting a first candidate history medical record of the plurality of candidate history medical records, and taking the first candidate history medical record as the first history reference medical record;
s634-2: obtaining a common grade sign index according to the first division result;
s634-3: performing matching calculation on the first historical reference medical records according to the common level sign indexes to obtain first matching indexes;
s634-4: constructing a first neighborhood of the first historical reference medical records based on a preset neighborhood scheme, wherein the first neighborhood comprises a plurality of candidate historical medical records;
s634-5: sequentially calculating the matching indexes of the plurality of candidate historical medical records to form a plurality of matching indexes;
S634-6: comparing the plurality of matching indexes, and screening a first optimal matching index of the first neighborhood;
s634-7: if the first optimal matching index is better than the first matching index, reversely matching the candidate history cases of the first optimal matching index, recording the candidate history cases as a second history reference case, and replacing the first history reference case with the second history reference case;
s634-8: and if the iterative optimization reaches the preset iterative times, outputting the first historical reference medical records.
Specifically, a first candidate history medical record of the plurality of candidate history medical records is extracted, and the first candidate history medical record is used as the first history reference medical record; obtaining a common grade sign index according to the first division result; performing matching calculation on the first historical reference medical records according to the common level sign indexes to obtain first matching indexes; constructing a neighborhood of the first historical reference medical records based on a preset neighborhood scheme, wherein the neighborhood comprises a plurality of candidate historical medical records; sequentially calculating the matching indexes of the plurality of candidate historical medical records to form a plurality of matching indexes; comparing the plurality of matching indexes, and screening a first optimal matching index of the first neighborhood; and if the first optimal matching index is better than the first matching index, reversely matching the candidate history cases of the first optimal matching index, recording the candidate history cases as a second history reference case, and replacing the first history reference case with the second history reference case.
And in the same scheme, based on the neighborhood of the second historical reference medical records, namely the second neighborhood, comparing the optimal matching indexes of the plurality of candidate historical medical records in the second neighborhood and the historical optimal group, and determining whether to replace the historical optimal group according to a comparison result, namely, performing iterative optimization based on the second neighborhood. Finally, when the iterative optimization reaches the preset iterative times, the historical optimal group obtained in the process is used as the first optimal conveying parameter.
The optimal conveying parameters are obtained through global iterative optimization by utilizing a tabu algorithm, so that the local optimal solution is jumped off, the quality of the optimal solution is improved, and the obtained historical reference medical records can be ensured to be closest to the current condition of the first patient, so that a detection treatment scheme with the most reference value is provided for medical staff, and the technical effect of providing reference for the medical staff to diagnose and treat the patient and ensuring the life safety of the patient is achieved.
Example two
Based on the same inventive concept as the intelligent detection method for night ward rounds in hospitals in the previous embodiments, as shown in fig. 4, the present application provides an intelligent detection system for night ward rounds in hospitals, wherein the system comprises:
A first construction unit 11, configured to collect first basic information of a first patient, and construct a first early warning scheme according to the first basic information;
a first obtaining unit 12, configured to perform format conversion on the first basic information to obtain a first dynamic two-dimensional code;
a second obtaining unit 13, configured to perform real-time vital sign detection on the first patient by using the smart wristband, to obtain first real-time vital sign information;
the first execution unit 14 is configured to update the first dynamic two-dimensional code in real time according to the first real-time physical sign information;
the first generating unit 15 is configured to scan and analyze the first dynamic two-dimensional code, and generate a first abnormal early warning according to the first early warning scheme;
a third obtaining unit 16, configured to traverse the history record based on the first abnormality pre-warning to obtain a first history reference medical record;
a first detection unit 17, configured to extract a first history detection record of the first history reference medical record, and perform a night ward inspection on the first patient based on the first history detection record.
Further, the system further comprises:
a fourth obtaining unit configured to obtain a first underlying disease and a first treatment regimen based on the first basic information;
The second generation unit is used for sequentially analyzing the influence conditions of the first basic disease and the first treatment scheme on the sign indexes of the patient and respectively generating a first influence sign index set and a second influence sign index set;
a third generating unit, configured to perform a union operation on the first influencing sign index set and the second influencing sign index set, and generate a preset influencing sign index set, where the preset influencing sign index set includes a plurality of sign indexes that change sign indexes of a patient;
a fifth obtaining unit, configured to sequentially analyze reasonable variation ranges of each of the plurality of physical sign indexes, and obtain a plurality of abnormal thresholds;
a first construction unit, configured to construct a sign index-abnormal threshold list according to the plurality of sign indexes and the plurality of abnormal thresholds;
the second construction unit is used for constructing the first early warning scheme according to the sign index-abnormal threshold list.
Further, the system further comprises:
a sixth obtaining unit, configured to scan the first dynamic two-dimensional code to obtain the first real-time sign information, where the first real-time sign information includes information of a plurality of real-time sign indexes;
A seventh obtaining unit, configured to sequentially analyze normal ranges of each of the plurality of real-time physical sign indexes based on the big data, to obtain a plurality of thresholds;
a third construction unit for constructing a list of sign indicators-threshold values from the plurality of sign indicators and the plurality of threshold values;
the second execution unit is used for extracting the real-time information of the first sign index according to the first real-time sign information;
a first judging unit, configured to judge whether the first sign indicator belongs to the preset influencing sign indicator set;
the second judging unit is used for obtaining a first abnormal threshold according to the physical sign index-abnormal threshold list and taking the first abnormal threshold as an early warning judging standard of the first physical sign index if the first physical sign index belongs to the preset influence physical sign index set;
and the fourth construction unit is used for constructing the first early warning scheme according to the early warning judgment standard.
Further, the system further comprises:
an eighth obtaining unit, configured to obtain a first threshold according to the sign index-threshold list if the first sign index does not belong to the preset influencing sign index set;
And the third execution unit is used for replacing the first abnormal threshold value by the first threshold value, namely, taking the first threshold value as the early warning judgment standard of the first sign index.
Further, the system further comprises:
a fifth construction unit, configured to construct a feature point set with the plurality of real-time physical sign indexes, the first underlying disease, and the first treatment plan as matching feature points, where the feature point set includes a plurality of feature points;
the fourth execution unit is used for acquiring historical medical records based on big data;
and a ninth obtaining unit, configured to traverse the history record according to the plurality of feature points, to obtain a first history reference medical record.
Further, the system further comprises:
a tenth obtaining unit, configured to perform importance level classification on the plurality of feature points according to importance degrees, to obtain a first classification result;
an eleventh obtaining unit, configured to obtain an importance level sign index according to the first division result;
the fifth execution unit is used for carrying out matching screening on the historical medical records according to the importance level sign indexes to obtain a candidate historical medical record set, wherein the candidate historical medical record set comprises a plurality of candidate historical medical records;
And a twelfth obtaining unit, configured to globally optimize the plurality of candidate historical medical records by using a tabu search, so as to obtain the first historical reference medical record.
Further, the system further comprises:
a sixth execution unit configured to extract a first candidate history case of the plurality of candidate history cases, and use the first candidate history case as the first history reference case;
a thirteenth obtaining unit, configured to obtain a common level sign indicator according to the first division result;
a fourteenth obtaining unit, configured to perform matching calculation on the first historical reference medical record according to the common level sign indicator, to obtain a first matching index;
a sixth construction unit, configured to construct a first neighborhood of the first history reference medical record based on a preset neighborhood scheme, where the first neighborhood includes a plurality of candidate history medical records;
the seventh execution unit is used for sequentially calculating the matching indexes of the plurality of candidate historical medical records to form a plurality of matching indexes;
the eighth execution unit is used for comparing the plurality of matching indexes and screening a first optimal matching index of the first neighborhood;
a ninth execution unit, configured to reversely match the candidate history cases of the first optimal matching index if the first optimal matching index is better than the first matching index, record as a second history reference case, and replace the first history reference case with the second history reference case;
And the tenth execution unit is used for outputting the first historical reference medical records if the iterative optimization reaches the preset iterative times.
Example III
Based on the same inventive concept as the intelligent detection method for night ward rounds in hospitals in the previous embodiments, the present application further provides a computer readable storage medium, on which a computer program is stored, which when executed by a processor, implements the method as in the first embodiment.
Exemplary electronic device
The electronic device of the present application is described below with reference to fig. 5.
Based on the same inventive concept as the intelligent detection method for night ward rounds in the foregoing embodiments, the present application further provides an intelligent detection device for night ward rounds in a hospital, including: a processor coupled to a memory for storing a program that, when executed by the processor, causes the system to perform the steps of the method of embodiment one.
The electronic device 300 includes: a processor 302, a communication interface 303, a memory 301. Optionally, the electronic device 300 may also include a bus architecture 304. Wherein the communication interface 303, the processor 302 and the memory 301 may be interconnected by a bus architecture 304; the bus architecture 304 may be a peripheral component interconnect (peripheral component interconnect, PCI) bus, or an extended industry standard architecture (extended industry Standard architecture, EISA) bus, among others. The bus architecture 304 may be divided into address buses, data buses, control buses, and the like. For ease of illustration, only one thick line is shown in fig. 5, but not only one bus or one type of bus.
Processor 302 may be a CPU, microprocessor, ASIC, or one or more integrated circuits for controlling the execution of the programs of the present application.
The communication interface 303 uses any transceiver-like means for communicating with other devices or communication networks, such as ethernet, radio access network (radio access network, RAN), wireless local area network (wireless local area networks, WLAN), wired access network, etc.
The memory 301 may be, but is not limited to, ROM or other type of static storage device that may store static information and instructions, RAM or other type of dynamic storage device that may store information and instructions, or may be an EEPROM (electrically erasable Programmable read-only memory), a compact disc-only memory (CD-ROM) or other optical disk storage, optical disk storage (including compact disc, laser disc, optical disc, digital versatile disc, blu-ray disc, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer. The memory may be self-contained and coupled to the processor through bus architecture 304. The memory may also be integrated with the processor.
The memory 301 is used for storing computer-executable instructions for executing the embodiments of the present application, and is controlled by the processor 302 to execute the instructions. The processor 302 is configured to execute computer-executable instructions stored in the memory 301, so as to implement an intelligent detection method for night ward rounds of hospitals according to the above embodiments of the present application.
Those of ordinary skill in the art will appreciate that: the various numbers of first, second, etc. referred to in this application are merely for ease of description and are not intended to limit the scope of this application nor to indicate any order. "and/or", describes an association relationship of an association object, and indicates that there may be three relationships, for example, a and/or B, and may indicate: a exists alone, A and B exist together, and B exists alone. The character "/" generally indicates that the context-dependent object is an "or" relationship. "at least one" means one or more. At least two means two or more. "at least one," "any one," or the like, refers to any combination of these items, including any combination of single item(s) or plural items(s). For example, at least one of a, b, or c (species ) may represent: a, b, c, a-b, a-c, b-c, or a-b-c, wherein a, b, c may be single or plural.
In the above embodiments, it may be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions described in the present application are produced in whole or in part. The computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatus. The computer instructions may be stored in or transmitted from one computer-readable storage medium to another, for example, by wired (e.g., coaxial cable, optical fiber, digital Subscriber Line (DSL)), or wireless (e.g., infrared, wireless, microwave, etc.). The computer readable storage medium may be any available medium that can be accessed by a computer or a data storage device including one or more servers, data centers, etc. that can be integrated with the available medium. The usable medium may be a magnetic medium (e.g., a floppy Disk, a hard Disk, a magnetic tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a Solid State Disk (SSD)), or the like.
The various illustrative logical units and circuits described herein may be implemented or performed with a general purpose processor, a digital signal processor, an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general purpose processor may be a microprocessor, but in the alternative, the general purpose processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices, e.g., a digital signal processor and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a digital signal processor core, or any other similar configuration.
The steps of a method or algorithm described in the present application may be embodied directly in hardware, in a software element executed by a processor, or in a combination of the two. The software elements may be stored in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. In an example, a storage medium may be coupled to the processor such that the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium may be integral to the processor. The processor and the storage medium may reside in an ASIC, which may reside in a terminal. In the alternative, the processor and the storage medium may reside in different components in a terminal. These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Although the present application has been described in connection with specific features and embodiments thereof, it will be apparent that various modifications and combinations can be made without departing from the spirit and scope of the application. Accordingly, the specification and figures are merely exemplary illustrations of the present application and are considered to cover any and all modifications, variations, combinations, or equivalents that fall within the scope of the present application. It will be apparent to those skilled in the art that various modifications and variations can be made in the present application without departing from the scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the present application and the equivalents thereof, the present application is intended to cover such modifications and variations.
Claims (6)
1. An intelligent detection method for night ward rounds of hospitals, the method being applied to an intelligent detection system for night ward rounds of hospitals, the system being in communication connection with a smart wristband, the method comprising:
collecting first basic information of a first patient, and constructing a first early warning scheme according to the first basic information;
performing format conversion on the first basic information to obtain a first dynamic two-dimensional code;
performing vital sign real-time detection on the first patient by using the intelligent wristband to obtain first real-time vital sign information;
According to the first real-time physical sign information, updating the first dynamic two-dimensional code in real time;
scanning and analyzing the first dynamic two-dimensional code, and generating a first abnormal early warning according to the first early warning scheme;
traversing the history medical records based on the first abnormal early warning to obtain a first history reference medical record;
extracting a first history detection record of the first history reference medical record, and performing night ward inspection on the first patient based on the first history detection record;
the constructing a first early warning scheme according to the first basic information includes:
obtaining a first underlying disease and a first treatment regimen based on the first underlying information;
sequentially analyzing the influence conditions of the first basic disease and the first treatment scheme on the sign indexes of the patient, and respectively generating a first influence sign index set and a second influence sign index set;
performing union operation on the first influence sign index set and the second influence sign index set to generate a preset influence sign index set, wherein the preset influence sign index set comprises a plurality of sign indexes of which the sign indexes of a patient change;
sequentially analyzing reasonable variation ranges of all the physical sign indexes to obtain a plurality of abnormal threshold values;
Constructing a sign index-abnormal threshold list according to the plurality of sign indexes and the plurality of abnormal thresholds;
constructing the first early warning scheme according to the sign index-abnormal threshold list, wherein the first early warning scheme comprises the following steps:
scanning the first dynamic two-dimensional code to obtain the first real-time sign information, wherein the first real-time sign information comprises information of a plurality of real-time sign indexes;
sequentially analyzing the normal range of each of the plurality of real-time physical sign indexes based on big data to obtain a plurality of thresholds;
constructing a sign index-threshold list according to the plurality of sign indexes and the plurality of thresholds;
extracting real-time information of a first sign index according to the first real-time sign information;
judging whether the first sign index belongs to the preset influence sign index set or not;
if the first physical sign index belongs to the preset influence physical sign index set, a first abnormal threshold value is obtained according to the physical sign index-abnormal threshold value list, and the first abnormal threshold value is used as an early warning judgment standard of the first physical sign index;
constructing the first early warning scheme according to the early warning judgment standard;
The traversing the history case record based on the first abnormal early warning to obtain a first history reference case comprises the following steps:
taking the real-time physical sign indexes, the first basic disease and the first treatment scheme as matching characteristic points to construct a characteristic point set, wherein the characteristic point set comprises a plurality of characteristic points;
acquiring a historical medical record based on big data;
traversing the history medical records according to the plurality of characteristic points to obtain a first history reference medical record;
the traversing the history medical records according to the plurality of characteristic points to obtain a first history reference medical record, which comprises the following steps:
performing importance level division on the plurality of feature points according to the importance degree to obtain a first division result;
obtaining an importance level sign index according to the first division result;
carrying out matching screening on the historical medical records according to the importance level sign indexes to obtain a candidate historical medical record set, wherein the candidate historical medical record set comprises a plurality of candidate historical medical records;
and performing global optimization on the plurality of candidate historical medical records by utilizing tabu search to obtain the first historical reference medical record.
2. The method of claim 1, wherein the determining whether the first physical sign indicator belongs to the set of preset influencing physical sign indicators further comprises:
if the first physical sign index does not belong to the preset influence physical sign index set, a first threshold value is obtained according to the physical sign index-threshold value list;
and replacing the first abnormal threshold by the first threshold, namely taking the first threshold as the early warning judgment standard of the first sign index.
3. The method of claim 2, wherein the globally optimizing the plurality of candidate historical medical records using a tabu search to obtain the first historical reference medical record comprises:
extracting a first candidate history medical record of the plurality of candidate history medical records, and taking the first candidate history medical record as the first history reference medical record;
obtaining a common grade sign index according to the first division result;
performing matching calculation on the first historical reference medical records according to the common level sign indexes to obtain first matching indexes;
constructing a first neighborhood of the first historical reference medical records based on a preset neighborhood scheme, wherein the first neighborhood comprises a plurality of candidate historical medical records;
Sequentially calculating the matching indexes of the plurality of candidate historical medical records to form a plurality of matching indexes;
comparing the plurality of matching indexes, and screening a first optimal matching index of the first neighborhood;
if the first optimal matching index is better than the first matching index, reversely matching the candidate history cases of the first optimal matching index, recording the candidate history cases as a second history reference case, and replacing the first history reference case with the second history reference case;
and if the iterative optimization reaches the preset iterative times, outputting the first historical reference medical records.
4. An intelligent detection system for night ward rounds of hospitals, the system comprising:
the first construction unit is used for collecting first basic information of a first patient and constructing a first early warning scheme according to the first basic information;
the first obtaining unit is used for carrying out format conversion on the first basic information to obtain a first dynamic two-dimensional code;
the second obtaining unit is used for detecting vital signs of the first patient in real time by utilizing the intelligent wristband to obtain first real-time sign information;
the first execution unit is used for updating the first dynamic two-dimensional code in real time according to the first real-time physical sign information;
The first generation unit is used for scanning and analyzing the first dynamic two-dimensional code and generating a first abnormal early warning according to the first early warning scheme;
the third obtaining unit is used for traversing the history medical records based on the first abnormal early warning to obtain a first history reference medical record;
the first detection unit is used for extracting a first history detection record of the first history reference medical record and carrying out night ward inspection detection on the first patient based on the first history detection record;
a fourth obtaining unit configured to obtain a first underlying disease and a first treatment regimen based on the first basic information;
the second generation unit is used for sequentially analyzing the influence conditions of the first basic disease and the first treatment scheme on the sign indexes of the patient and respectively generating a first influence sign index set and a second influence sign index set;
a third generating unit, configured to perform a union operation on the first influencing sign index set and the second influencing sign index set, and generate a preset influencing sign index set, where the preset influencing sign index set includes a plurality of sign indexes that change sign indexes of a patient;
a fifth obtaining unit, configured to sequentially analyze reasonable variation ranges of each of the plurality of physical sign indexes, and obtain a plurality of abnormal thresholds;
A first construction unit, configured to construct a sign index-abnormal threshold list according to the plurality of sign indexes and the plurality of abnormal thresholds;
the second construction unit is used for constructing the first early warning scheme according to the sign index-abnormal threshold list;
a sixth obtaining unit, configured to scan the first dynamic two-dimensional code to obtain the first real-time sign information, where the first real-time sign information includes information of a plurality of real-time sign indexes;
a seventh obtaining unit, configured to sequentially analyze normal ranges of each of the plurality of real-time physical sign indexes based on the big data, to obtain a plurality of thresholds;
a third construction unit for constructing a list of sign indicators-threshold values from the plurality of sign indicators and the plurality of threshold values;
the second execution unit is used for extracting the real-time information of the first sign index according to the first real-time sign information;
a first judging unit, configured to judge whether the first sign indicator belongs to the preset influencing sign indicator set;
the second judging unit is used for obtaining a first abnormal threshold according to the physical sign index-abnormal threshold list and taking the first abnormal threshold as an early warning judging standard of the first physical sign index if the first physical sign index belongs to the preset influence physical sign index set;
A fourth construction unit, configured to construct the first early warning scheme according to the early warning judgment standard;
a fifth construction unit, configured to construct a feature point set with the plurality of real-time physical sign indexes, the first underlying disease, and the first treatment plan as matching feature points, where the feature point set includes a plurality of feature points;
the fourth execution unit is used for acquiring historical medical records based on big data;
a ninth obtaining unit, configured to traverse the history record according to the plurality of feature points, to obtain a first history reference medical record;
a tenth obtaining unit, configured to perform importance level classification on the plurality of feature points according to importance degrees, to obtain a first classification result;
an eleventh obtaining unit, configured to obtain an importance level sign index according to the first division result;
the fifth execution unit is used for carrying out matching screening on the historical medical records according to the importance level sign indexes to obtain a candidate historical medical record set, wherein the candidate historical medical record set comprises a plurality of candidate historical medical records;
and a twelfth obtaining unit, configured to globally optimize the plurality of candidate historical medical records by using a tabu search, so as to obtain the first historical reference medical record.
5. An intelligent detection device for night ward rounds of hospitals, comprising: a processor coupled to a memory for storing a program which, when executed by the processor, causes the system to perform the steps of the method of any one of claims 1 to 3.
6. A computer-readable storage medium, characterized in that the storage medium has stored thereon a computer program which, when executed by a processor, implements the steps of the method according to any of claims 1 to 3.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210465887.6A CN114842935B (en) | 2022-04-29 | 2022-04-29 | Intelligent detection method and system for night ward round of hospital |
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