Comparative analysis of clinical feature–based machine learning models for predicting myofascial pelvic pain syndrome: a single-center retrospective study

Machine learning models, particularly the random forest algorithm, demonstrated strong potential for accurately predicting MPPS, supporting early diagnosis and enabling personalized clinical decision-making for women affected by this condition.