Emergency clinical diagnosis analysis system based on Bayesian probability inference

Abstract

,The invention relates to the technical field of medical intelligent clinical diagnosis and analysis, and particularly discloses an emergency clinical diagnosis analysis system based on Bayesian probability inference. An information acquisition unit is arranged to acquire electronic medical record (EMR) data of a patient in a medical emergency clinical process; an entity extraction unit and a data integration unit are arranged to integrate the multi-source data; then a text feature extraction unit is arranged to put the integrated multi-dimensional heterogeneous data into an ALBERT model for training so as to extract text features of electronic cases; and then, a Bayesian probability calculation module is arranged to map the text features and the probability of a DNF model (a differentiated generation model) to a Bayesian space so as to construct a Bayesian probability model, the optimal probability of diagnosis and emergency treatment measures is obtained through probability calculation so as to provide emergency clinical diagnosis support (final probability inference results are Top-1 and Top-3), and the support can be applied to emergency clinical diagnosis of various diseases as a reference.

Description

technical field [0001] The invention relates to the technical field of medical intelligent analysis, in particular to an emergency clinical diagnosis analysis system based on Bayesian probability inference. Background technique [0002] At present, China has a large population, facing the problem that the number of doctors is not directly proportional to the population, and the number of emergency doctors is small, and the time cost of seeing a doctor is high, but emergency treatment requires fast time. In response to this, intelligent diagnosis came into being, but automatic diagnosis based on medical record text is still a difficult clinical task, because it needs to strike a proper balance between accuracy and interpretability, and lacks explanation for the diagnosed disease. It is still a difficult problem to solve the problem of explaining its diagnosis and disease prediction. At present, China has a population of 1.4 billion, but only 2 million grassroots doctors. For...

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Problems solved by technology

In response to this, intelligent diagnosis came into being, but automatic diagnosis based on medical record text is still a difficult clinical task, because it needs to strike a proper balance between accuracy and interpretability, and lacks explanation for the diagnosed disease. It is still a difficult problem to explain the prediction of its diagnosis and disease

At present, China has a population of 1.4 billion, but only 2 million grassroots doctors. For grassroots doctors, the most lacking is the experience and wisdom of medical experts. With the assistance of intelligent medical care, they can use the experience and wisdom of experts Carry out large-scale replication, let these become the coaches of grass-roots doctors, improve the medical skills of grass-roots doctors, and lead to qualitative changes through quantitative changes, and truly promote the improvement of medical standards. However, there is currently no such mature emergency treatment based on medical records. Clinical Automatic Diagnosis Technology

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