Artificial intelligence auxiliary diagnosis and treatment system and construction method thereof, equipment and storage medium

Abstract

The invention discloses an artificial intelligence auxiliary diagnosis and treatment system and a construction method thereof, equipment and a storage medium and belongs to the technical field of lifehealth. The system includes a disease knowledge map module, a disease diagnosis model module and a machine learning decision module, wherein the disease knowledge map module is configured to collectvarious resources about diseases and form a disease knowledge database for querying and reading, the disease diagnosis model module is configured to receive the patient information, store the information in the system database, input the information to the machine learning decision module, extract indicator data from the disease knowledge map module through the machine learning decision module toperform comparative analysis, push a patient information set and suggest an examination which a patient needs to take and a scheme set of related drug treatment for choose of doctors. The system is advantaged in that the underlying knowledge map is comprehensive and authoritative, interaction operation is simple, use efficiency is high, on the human-computer interaction level, the intelligence degree is high.

Description

technical field [0001] The present invention relates to the technical field of life and health, and in particular to an artificial intelligence-assisted diagnosis and treatment system and its construction method, equipment and storage medium. Background technique [0002] According to the World Health Organization survey, a large number of patients worldwide die from medical errors rather than the disease itself. In 1999, IOM (National Institute of Medicine) published an epoch-making report "Toerris Human" (people make mistakes), the report shows: First, the number of medical errors is alarming, and medical errors are among the top ten causes of death Ranked fifth; second, most of the medical errors come from human factors, which can be avoided by computer systems. In 2013, an analysis published in the American journal Patient safety & quality healthcare estimated that 210,000 to 440,000 people died of medical accidents in the United States every year, making it the third l...

AI Technical Summary

Problems solved by technology

[0006] Through the analysis of the above content, it can be known that the existing medical diagnosis system has the following technical problems: 1) It cannot do artificial intelligence-assisted diagnosis and treatment well, but only provides doctors with reference to the inspection items, inspection items, surgical items, and therapeutic drugs of certain types of diseases etc.; the underlying knowledge graph is not comprehensive and authoritative enough; 2) It cannot reduce the workload of doctors; 3) It cannot provide clinical diagnosis and treatment paths for similar diseases through the system; 4) It cannot allow patients to move according to certain changes in their bodies 5) The misdiagnosis rate of doctors cannot be greatly reduced, and the diagnosis and treatment experience data cannot be shared to remote mountainous areas

To sum up, the underlying knowledge map based on the existing consultation system is not comprehensive and authoritative; there are problems such as complex operation and low efficiency in the interaction; in terms of human-computer interaction, the degree of intelligence is insufficient

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