Evaluation of Machine Learning Classifiers in Identifying Erythemato-Squamous Diseases

This research pioneers a machine learning-enhanced diagnostic system for erythemato-squamous diseases (ESD), utilizing Naive Bayes, Random Forest, and Support Vector Machine (SVM) algorithms to categorize various ESD types. The system, leveraging a dataset inclusive of clinical, historical, and demographic data, attained a remarkable 98.64% accuracy rate with SVM, underscoring its potential to significantly refine ESD diagnosis and treatment modalities. Subsequent validation against an additional dataset corroborated its reliability, heralding substantial progress in dermatological healthcare and pioneering new avenues for the application of machine learning in medical diagnostics.