Patient death risk prediction method and system based on electronic medical record, terminal and readable storage medium

An electronic medical record, risk prediction technology, applied in prediction, patient-specific data, neural learning methods, etc., to achieve the effect of complete extraction, enhanced interpretability, and accurate death risk prediction

Pending Publication Date: 2022-01-07
CENT SOUTH UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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  • Patient death risk prediction method and system based on electronic medical record, terminal and readable storage medium
  • Patient death risk prediction method and system based on electronic medical record, terminal and readable storage medium
  • Patient death risk prediction method and system based on electronic medical record, terminal and readable storage medium

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Embodiment 1

[0056] The content and construction process of the patient death risk prediction model of the present invention will be described first below. The construction process of the patient death risk prediction model is as follows: 1. Construct the data set based on the patient's electronic medical record; 2. Use the patient's death result in the data set as the training label, process the patient's medical characteristic data in the data set according to the following steps S1-S4 and The network training was carried out to obtain the prediction model of the patient's death risk.

[0057] Regarding the data set used in model training, in this embodiment, the data set includes laboratory test data set, vital sign data set and medication record set as examples for illustration. It should be understood that in other feasible embodiments, according to medical record data characteristics, and other types of patient medical characteristic data can also be selected in the data set, which i...

Embodiment 2

[0115] This embodiment provides a system based on the above-mentioned method for predicting the risk of death of a patient, which includes: a data acquisition module, a model acquisition module, and a prediction module.

[0116] Wherein, the data acquisition module is used to acquire the electronic medical records of the patients to be predicted;

[0117] A model acquisition module, used to acquire a trained patient death risk prediction model;

[0118] The prediction module is used to obtain the patient's death prediction result based on the patient's electronic medical record and the patient's death risk prediction model.

[0119] In some implementations, the patient death risk prediction model includes a data preprocessing layer, a time series model learning layer, a heterogeneous data fusion presentation layer, and a death risk prediction layer, and then performs data processing and result prediction according to steps S1-S4 .

[0120] In some implementations, if the pat...

Embodiment 3

[0125] This embodiment provides a terminal, which includes: one or more processors and a memory storing one or more computer programs. Wherein, the processor invokes the computer program to execute: the steps of a method for predicting patient death risk based on electronic medical records.

[0126] For the patient to be predicted, the processor invokes the computer program to perform:

[0127] Step 1: Obtain the electronic medical record of the patient to be predicted;

[0128] Step 2: Obtain the patient's death prediction result based on the patient's electronic medical record and the patient's death risk prediction model.

[0129] Wherein, after obtaining the electronic medical record of the patient to be predicted, the processor invokes the computer program to specifically execute:

[0130] S1: Data preprocessing, preprocessing the electronic medical record data of the patient to be predicted;

[0131] S2: Time-series model learning: According to the time-series charact...

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Abstract

The invention discloses a patient death risk prediction method and system based on an electronic medical record, a terminal and a readable storage medium. According to the patient death risk prediction model constructed by the method, the time information is added to the medical feature data to obtain the patient feature data with the time characteristic, then the time sequence model is utilized to learn feature representation of various types of patient feature data, an irregular time pattern is mined, and the patient death risk prediction accuracy is improved. According to the method, the feature data of a patient is extracted, then an attention mechanism with a hierarchical structure is introduced to fuse the heterogeneous feature data to obtain a more comprehensive fused feature, and finally, the fused representation of the patient is applied to death risk prediction, so that the model prediction precision and reliability are improved. According to the method, the irregular time sequence modeling problem and the multivariate heterogeneous data fusion problem in the prior art are effectively solved, the method and other methods are tested and compared on the same data set, and experimental results show that the method has good performance in the aspect of death risk prediction of critical patients.

Description

technical field [0001] The invention belongs to the field of artificial intelligence and medical applications, and in particular relates to a method, system, terminal and readable storage medium for predicting patient death risk based on electronic medical records. Background technique [0002] The Intensive Care Unit (ICU) usually concentrates the most important resources of the hospital, such as departments, medical equipment and personnel, with the purpose of providing high-quality and comprehensive diagnosis and treatment services for critically ill patients, so as to reduce the mortality of patients. The in-hospital mortality rate of critically ill patients is easily affected by hospital resources and patients' own conditions. Globally, the mortality rate of patients in intensive care units remains high, and the high cost of diagnosis and treatment has greatly increased the living burden of patients and their families. Realizing the prediction of the death risk of pati...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G16H10/60G16H50/30G16H50/70G06K9/62G06N3/04G06N3/08
CPCG06Q10/04G16H50/30G16H50/70G16H10/60G06N3/08G06N3/045G06F18/253
Inventor 安莹刘洋盛羽陈先来
Owner CENT SOUTH UNIV
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