Intelligent decision analysis system and method for clinical diagnosis and treatment

Abstract

The invention provides an intelligent decision analysis system and method for clinical diagnosis and treatment. A clinical diagnosis and treatment knowledge base module stores various clinical diagnosis and treatment knowledge in a unified representation form; wherein the clinical evaluation module takes the clinical manifestation of the new patient as input, and executes a rule reasoning mechanism to output an evaluation result of the new patient; then the clinical treatment scheme decision module analyzes the clinical manifestation of the new patient and the similarity between clinical evaluation and historical cases by utilizing clinical diagnosis and treatment guidelines and case literature report knowledge in the clinical diagnosis and treatment knowledge base module and combining the evaluation result output by the clinical evaluation module, and finds out a diagnosis and treatment case most similar to the new patient. and according to the treatment scheme of the most similar diagnosis and treatment case, an example is provided for treatment of a new patient. According to the method, a large amount of differentiated data in the specific disease diagnosis and treatment field can be effectively classified and sorted, so that a more efficient and reliable disease diagnosis and treatment result is provided for a patient in combination with doctor expert experience and an intelligent auxiliary decision making system.

Description

technical field [0001] The invention relates to the field of intelligent evaluation and treatment of clinical assistant decision-making, in particular to an intelligent decision-making analysis system and method for clinical diagnosis and treatment. Background technique [0002] At present, people's demand for clinical medical resources is increasing. At the same time, human resources such as experts, doctors and nurses in the domestic medical field and other medical resources are still relatively scarce, and the quality and efficiency of clinical medical treatment still need to be improved. Traditional methods of clinical inquiry, triage, assessment, and treatment rely on the experience of doctors and the guidelines provided by experts based on evidence-based medicine, but there are problems such as low efficiency, inaccuracy and objectivity. It is difficult for doctors to obtain accurate and reliable evaluation results in a short period of time during the stages of consult...

AI Technical Summary

Problems solved by technology

However, the above scheme cannot realize feature selection and correlation calculation.

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