[Comprehensive evaluation of medical process by constructed polynory function]

Area of Science:

• Medical Informatics
• Fuzzy Set Theory Applications
• Health Services Research

Background:

• Evaluating complex medical processes is challenging.
• Existing methods may lack the flexibility to handle uncertainty in patient data.
• A robust framework is needed for comprehensive medical process assessment.

Purpose of the Study:

• To introduce and validate a novel "medical process evaluation" model.
• To apply the model to prognostic evaluation of acute myocardial infarction patients.
• To assess the efficacy of pneumoconiosis treatments.

Main Methods:

• Developed a model based on constructed polynory functions.
• Utilized Fuzzy Set theory for handling imprecise medical data.
• Applied the model to retrospective patient data for validation.

Main Results:

• The model provided satisfactory prognostic evaluations for myocardial infarction patients.
• Comprehensive efficacy evaluations for pneumoconiosis treatments were achieved.
• Demonstrated the model's effectiveness in real-world clinical scenarios.

Conclusions:

• The proposed Fuzzy Set theory-based model is effective for medical process evaluation.
• The model framework shows potential for generalization to diverse medical applications.
• This approach offers a valuable tool for improving healthcare outcome assessments.