Perioperative critical adverse event intervention decision-making method based on Bayesian network and utility system

Abstract

The invention relates to a perioperative period critical adverse event intervention decision-making method based on a Bayesian network and a utility system, and belongs to the field of artificial intelligence and medical application thereof, and the method comprises the steps: S1, constructing a perioperative period critical adverse event intervention measure set; S2, giving a utility value to each intervention measure to form an intervention measure utility system; S3, constructing an expert knowledge base for the intervention measures; S4, forming a plurality of combined intervention schemes; S5, constructing a Bayesian network model intervened by critical adverse events in the perioperative period based on the clinical case data and source of the patient and expert knowledge; S6, for asingle patient, inputting data information of the perioperative period as data evidences of a Bayesian network model, and executing Bayesian network reasoning to obtain a probability value whether each intervention measure is taken or not; S7, calculating a total utility value of each combination scheme; S8, selecting a combination scheme with the total utility value of Top-3 as a recommendation result of the intervention decision scheme.

Description

technical field [0001] The invention belongs to the field of artificial intelligence and its medical application, and relates to a perioperative critical adverse event intervention method based on Bayesian network and utility system. Background technique [0002] The application of artificial intelligence in the medical field is becoming more and more popular. In order to promote the establishment of a fast and accurate intelligent medical system, the medical industry urgently needs to carry out preface technology applications, actively and quickly use artificial intelligence technology, fully integrate medical data and medical expert experience, and speed up the perioperative period. The promotion and application of new models and methods of artificial intelligence treatment can improve medical efficiency and quality, and promote people's livelihood, health and safety. The clinical intervention of critical adverse events in the perioperative period needs to be based on the ...

AI Technical Summary

Problems solved by technology

The clinical intervention of critical adverse events in the perioperative period needs to be based on the specific situation of the patient and rely on the rich experience of medical experts to make decisions. The requirements for medical staff are high and the efficiency is not high.

At present, some breakthroughs have been made in the clinical intervention of critical adverse events in the perioperative period by using artificial intelligence methods, such as some clinical decision support systems, but these methods only provide conventional intervention methods and do not fully consider the specific conditions of patients , did not fully analyze the impact of the intervention on the patient's rehabilitation and physical damage

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