CN112331325A - Basic life support decision-making system under artificial intelligence - Google Patents
Basic life support decision-making system under artificial intelligence Download PDFInfo
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- CN112331325A CN112331325A CN202011123861.0A CN202011123861A CN112331325A CN 112331325 A CN112331325 A CN 112331325A CN 202011123861 A CN202011123861 A CN 202011123861A CN 112331325 A CN112331325 A CN 112331325A
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- 238000013473 artificial intelligence Methods 0.000 title claims abstract description 16
- 238000012544 monitoring process Methods 0.000 claims abstract description 49
- 238000011282 treatment Methods 0.000 claims abstract description 30
- 230000002159 abnormal effect Effects 0.000 claims abstract description 17
- 210000002345 respiratory system Anatomy 0.000 claims abstract description 7
- 206010002091 Anaesthesia Diseases 0.000 claims abstract description 6
- 230000037005 anaesthesia Effects 0.000 claims abstract description 6
- 230000036760 body temperature Effects 0.000 claims abstract description 5
- 206010021118 Hypotonia Diseases 0.000 claims abstract description 4
- 230000036640 muscle relaxation Effects 0.000 claims abstract description 4
- 238000001514 detection method Methods 0.000 claims description 8
- 238000012937 correction Methods 0.000 claims description 7
- 230000036772 blood pressure Effects 0.000 claims description 4
- 230000000241 respiratory effect Effects 0.000 claims description 4
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 claims description 3
- 230000000747 cardiac effect Effects 0.000 claims description 3
- 229910052760 oxygen Inorganic materials 0.000 claims description 3
- 239000001301 oxygen Substances 0.000 claims description 3
- 238000006213 oxygenation reaction Methods 0.000 claims description 3
- 230000002792 vascular Effects 0.000 claims description 3
- 210000003462 vein Anatomy 0.000 claims description 3
- 230000008859 change Effects 0.000 abstract description 2
- 230000006872 improvement Effects 0.000 description 8
- 230000005856 abnormality Effects 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000004075 alteration Effects 0.000 description 1
- 238000003745 diagnosis Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000000034 method Methods 0.000 description 1
- 230000000474 nursing effect Effects 0.000 description 1
- 230000029058 respiratory gaseous exchange Effects 0.000 description 1
- 230000006641 stabilisation Effects 0.000 description 1
- 238000011105 stabilization Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 230000004083 survival effect Effects 0.000 description 1
- 208000024891 symptom Diseases 0.000 description 1
- 239000002699 waste material Substances 0.000 description 1
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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
- G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
- G16H40/60—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices
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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
- 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
- G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
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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
- 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
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Abstract
The invention discloses a basic life support decision-making system under artificial intelligence, which comprises a monitoring end, a decision-making system and an output end, wherein the monitoring end is connected with the decision-making system; the monitoring end comprises a circulatory system monitoring module, a respiratory system monitoring module, a body temperature monitoring module, an anesthesia depth monitoring module and a muscle relaxation monitoring module, monitors vital sign data of a patient and transmits the vital sign data to the decision-making system; the decision system automatically identifies the abnormal condition of the vital sign according to the data collected by the monitoring end, makes reason analysis and judgment and generates a decision scheme; and the output end outputs the decision scheme generated by the decision system. The invention can clearly classify the monitoring indexes and is convenient to observe; the decision system classifies the abnormal indexes independently, omission is not easy to occur, medical decisions are automatically generated according to the physical signs and the treatment guidelines, and doctors can select or change the medical decisions, so that the working intensity of the doctors is reduced.
Description
Technical Field
The invention relates to the technical field of medical instruments, in particular to a basic life support decision-making system under artificial intelligence.
Background
The human body has four vital signs, blood pressure, heart rate, respiration and body temperature. Vital sign stabilization is a prerequisite for survival. This is also the most basic indicator during anesthesia of a patient and during intensive care unit treatment. Maintaining vital signs stable is also a fundamental strategy for clinical treatment by clinicians.
At present, the monitoring means of vital signs are respectively carried out, and instruments used for monitoring are also provided by different manufacturers. Currently, there are more and more clinical monitoring items for the respiratory or circulatory system. The clinician must find the abnormality of the patient's physical signs through his or her close observation, then make comprehensive analysis according to his or her own medical knowledge and clinical experience, and finally make a treatment decision. This mode of operation suffers from the following disadvantages:
1. due to the fact that monitoring projects are numerous, the monitored data volume is large, and some monitoring data and information with important values can be omitted through manual observation;
2. at present, treatment methods for a plurality of symptoms are standardized and clarified, but the fields in which clinicians are skilled are limited, and the treatment details of each clinical sign cannot be completely mastered, so that deviation of treatment effects occurs;
3. the physical sign data of the patient are finally processed by the doctor, the burden of medical staff is increased, and the working efficiency of the doctor is reduced and even decision deviation is generated due to long-time fatigue work;
4. the monitoring needs a plurality of machines and monitoring equipment, and the equipment can occupy a large amount of areas of operating rooms or monitoring wards, and certain obstacles are generated to the normal treatment and nursing work of medical staff.
In summary, a patient in an anesthesia period or an intensive care unit needs a system which can integrate and monitor vital signs, automatically analyze and judge abnormal data of the vital signs, automatically make a decision, and to a certain extent help a doctor to complete a final treatment decision.
Disclosure of Invention
The invention aims to overcome the problems and provide a basic life support decision-making system under artificial intelligence. In order to achieve the purpose, the invention adopts the following technical scheme:
a basic life support decision-making system under artificial intelligence comprises a monitoring end, a decision-making system and an output end;
the monitoring end at least comprises a circulatory system monitoring module, a respiratory system monitoring module, a body temperature monitoring module, an anesthesia depth monitoring module and a muscle relaxation monitoring module, and monitors vital sign data of a patient and transmits the vital sign data to the decision-making system;
the decision system automatically identifies the abnormal condition of the vital sign according to the data collected by the monitoring end, makes reason analysis and judgment and generates a decision scheme;
and the output end outputs the decision scheme generated by the decision system.
As an improvement, the circulatory system detection module detects blood pressure, central veins, cardiac output, vascular resistance, electrocardiograms and the like.
As an improvement, the respiratory system detection module detects oxygenation indexes, respiratory kinetic parameters, oxygen concentration and the like.
As an improvement, a normal value range of the detection data is preset in the decision system, and normal data and abnormal data are classified according to the normal value range.
As an improvement, the decision system uniformly lists abnormal values and automatically generates treatment decisions according to the data of the abnormal values and treatment guidelines of the corresponding signs of the data.
As an improvement, a correction end is arranged in the decision-making system, and a doctor corrects a decision-making treatment decision through the correction end.
As an improvement, the decision system outputs the abnormality data and the treatment decision to an output.
As an improvement, the system is also provided with a learning module, and the learning module collects abnormal data and treatment decisions corrected by doctors and intelligently corrects subsequent monitoring treatment.
As an improvement, the output end generates monitoring records and medical advice according to a decision-making system.
As a refinement, the output is also connected to the HIS system of the hospital.
The invention has the advantages that:
1. the invention can clearly classify the monitoring indexes and is convenient to observe;
2. abnormal indexes are classified independently, so that omission is not easy to generate;
3. medical decision is automatically generated according to the physical sign and the treatment guide, and a doctor can select or change the medical decision to reduce the working intensity of the doctor;
4. the vital signs are integrally monitored and intelligently decided, so that the treatment is more standard;
5. the monitoring equipment is combined in a centralized mode, and waste of sites is reduced.
Drawings
FIG. 1 is a schematic diagram showing the operation of embodiment 1;
fig. 2 is a schematic diagram of the operation in embodiment 2.
Detailed Description
The present invention will be described in detail and specifically with reference to the following examples so as to facilitate the understanding of the present invention, but the following examples do not limit the scope of the present invention.
Example 1
The embodiment discloses a basic life support decision-making system under artificial intelligence, which comprises a monitoring end, a decision-making system and an output end.
The monitoring end at least comprises a circulatory system monitoring module, a respiratory system monitoring module, a body temperature monitoring module, an anesthesia depth monitoring module and a muscle relaxation monitoring module, and monitors vital sign data of a patient and transmits the vital sign data to the decision-making system. The circulatory system detection module detects blood pressure, central veins, cardiac output, vascular resistance, electrocardiogram and the like. The respiratory system detection module detects oxygenation indexes, respiratory kinetic parameters, oxygen concentration and the like.
The decision-making system automatically identifies the abnormal condition of the vital signs according to the data collected by the monitoring end, makes reason analysis and judgment and generates a decision-making scheme. The decision system is preset with a normal value range of the detection data, and normal data and abnormal data are classified according to the normal value range. The decision-making system lists the abnormal values uniformly and automatically generates treatment decisions according to the data of the abnormal values and treatment guidelines of the corresponding signs of the data. And a correction end is also arranged in the decision-making system, and a doctor corrects a decision-making treatment decision through the correction end. The decision system outputs the anomaly data and the treatment decision to an output.
And the output end outputs the decision scheme generated by the decision system. The output end is also connected to the HIS system of the hospital, and generates information such as monitoring records and medical orders.
Example 2
The embodiment discloses a basic life support decision-making system under artificial intelligence.
The embodiment is also provided with a learning module, and the learning module collects abnormal data and treatment decisions corrected by doctors and intelligently corrects subsequent monitoring treatment. The other structure of this embodiment is the same as embodiment 1.
In the embodiment, the learning module is arranged, so that the final decision generated by the system is continuously intelligently corrected, and the accuracy of the decision system intelligently generated by the decision system is continuously enhanced. The diagnosis and treatment efficiency of the doctor on the patient is improved.
The embodiments of the present invention have been described in detail above, but they are merely exemplary, and the present invention is not equivalent to the above described embodiments. Any equivalent modifications and substitutions to those skilled in the art are also within the scope of the present invention. Accordingly, it is intended that all equivalent alterations and modifications be included within the scope of the invention, without departing from the spirit and scope of the invention.
Claims (10)
1. A basic life support decision-making system under artificial intelligence is characterized by comprising a monitoring end, a decision-making system and an output end;
the monitoring end at least comprises a circulatory system monitoring module, a respiratory system monitoring module, a body temperature monitoring module, an anesthesia depth monitoring module and a muscle relaxation monitoring module, and monitors vital sign data of a patient and transmits the vital sign data to the decision-making system;
the decision system automatically identifies the abnormal condition of the vital sign according to the data collected by the monitoring end, makes reason analysis and judgment and generates a decision scheme;
and the output end outputs the decision scheme generated by the decision system.
2. The system of claim 1, wherein the circulatory system detection module detects blood pressure, central veins, cardiac output, vascular resistance, and electrocardiogram.
3. The artificial intelligence underlying basic life support decision making system of claim 1, wherein the respiratory system detection module detects oxygenation indicators, respiratory drive parameters, oxygen concentration, and the like.
4. The artificial intelligence basic life support decision making system according to claim 1, wherein a normal value range of the detected data is preset in the decision making system, and normal data and abnormal data are classified according to the normal value range.
5. An artificial intelligence basic life support decision making system according to claim 4, wherein the decision making system lists outliers in a unified way and automatically generates treatment decisions based on data of the outliers and treatment guidelines for signs corresponding to the data.
6. The artificial intelligence basic life support decision making system according to claim 5, wherein a correction end is provided in the decision making system, and a doctor modifies decision making treatment decisions by the correction end.
7. An artificial intelligence based basic life support decision making system according to claim 4 or 5, wherein the decision making system outputs anomaly data and treatment decisions to an output.
8. The system of claim 4 or 5, wherein the system further comprises a learning module, and the learning module collects abnormal data and doctor-corrected treatment decisions, and makes intelligent corrections to subsequent monitored treatments.
9. The artificial intelligence basic life support decision making system according to claim 1, wherein said output generates monitoring records and medical orders according to the decision making system.
10. The artificial intelligence underlying basic life support decision system according to claim 1, wherein the output is further connected to a HIS system of a hospital.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011123861.0A CN112331325A (en) | 2020-10-20 | 2020-10-20 | Basic life support decision-making system under artificial intelligence |
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| CN202011123861.0A CN112331325A (en) | 2020-10-20 | 2020-10-20 | Basic life support decision-making system under artificial intelligence |
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| CN112331325A true CN112331325A (en) | 2021-02-05 |
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| CN202011123861.0A Pending CN112331325A (en) | 2020-10-20 | 2020-10-20 | Basic life support decision-making system under artificial intelligence |
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- 2020-10-20 CN CN202011123861.0A patent/CN112331325A/en active Pending
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Application publication date: 20210205 |