A Fuzzy Logic-Based Computational Framework for Precision Triage in Androgenetic Alopecia: A Simulated Biomarker-Driven Approach

The study introduces a fuzzy logic-based computational framework, the TPAP method, for precision triage in androgenetic alopecia (AGA) using a dataset of 100 patients. This framework categorizes patients into seven triage levels based on 11 criteria, achieving an overall accuracy of 76% and 88% accuracy for severe cases. It outperformed traditional models like logistic regression and decision trees, effectively managing imbalanced data and aligning with clinical expertise. The study emphasizes the importance of bioactive markers correlated with disease severity and suggests that while TPAP shows promise, further validation with real-world data is needed. Future research will focus on hybrid approaches and machine learning integration to enhance the model's accuracy and applicability.