Machine learning-based prediction of Sasang constitution types using comprehensive clinical information and identification of key features for diagnosis

摘要

Despite the importance of accurate Sasang type diagnosis, a unique form of Korean medicine, there have been concerns about consistency among diagnoses. We investigate a data-driven integrative diagnostic model by applying machine learning to a multicenter clinical dataset with comprehensive features.