Time window cutting-based health risk key event detection method and system

A key event, time window technology, applied in diagnostic recording/measurement, medical science, diagnosis, etc., can solve problems such as lack, poor evaluation effect, and complex mortality risk evaluation

Active Publication Date: 2021-01-12
PEKING UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the assessment of mortality risk is very complicated. It needs to comprehensively analyze multiple physiological indicators of the patient, consider static information such as the patient's age, gender, and past medical history, and combine a large amount of medical knowledge to make the f...

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  • Time window cutting-based health risk key event detection method and system
  • Time window cutting-based health risk key event detection method and system
  • Time window cutting-based health risk key event detection method and system

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Embodiment Construction

[0050] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0051] references

[0052] Ma L, Zhang C, Wang Y, et al. Concare: Personalized clinical feature embedding via capturing the healthcare context[C] / / Proceedings of the AAAI Conference on Artificial Intelligence. 2020,34(01):833-840.

[0053] Terminology Explanation

[0054] electronic medical records

[0055] Electronic Medical Record (EMR, Electronic Medical Record) is also called a computerized medical record system or a computer-based patient record. It is a digital medical record that is saved, managed, transmitted and reproduced by electronic devices (computers, health cards, etc.) to replace handwritten paper medical records. Its content includes all the information of paper medical records.

[0056] Physiological indicators important index

[0057] By inputting the electronic medical record data of the patient's previous n v...

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Abstract

The invention discloses a time window cutting-based health risk key event detection method and system. The method comprises the following steps: S100, inputting an electronic medical record of a patient into a trained deep learning model to obtain important indexes and death risk indexes of physiological indexes of a patient every time the patient sees a doctor; S200, dividing targets of detectionof health risk key events of the patient into four types according to time windows, detecting the four types on the basis of the obtained important index and the death risk index of each physiological index to screen out the physiological indexes of the health risk key events which need to be proposed; and S300, based on a visual interface, displaying the detection process and detection results of the health risk key events of the patient. The method and system can mine more valuable information with reference significance from data of the electronic medical record of the patient in the hospital to help the doctor make diagnosis.

Description

technical field [0001] The invention relates to the field of health risk detection, in particular to a method and system for detecting key health risk events based on time window cutting. Background technique [0002] For end-stage patients with chronic diseases and critically ill patients, assessing their risk of death will help medical staff to take targeted treatment measures as soon as possible to improve the survival probability of patients. However, the assessment of mortality risk is very complicated. It needs to comprehensively analyze multiple physiological indicators of the patient, consider static information such as the patient's age, gender, and past medical history, and combine a large amount of medical knowledge to make the final judgment. Only those with rich medical knowledge and rich clinical experience Doctors can get more accurate evaluation results only after investing a lot of time and energy. However, in clinical practice, medical institutions often h...

Claims

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Application Information

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IPC IPC(8): A61B5/00
CPCA61B5/7292A61B5/7246
Inventor 王亚沙马连韬余志浩焦贤锋周佳慧马辛宇
Owner PEKING UNIV
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