Liver Disorders and Pitta Dosha in Ayurveda Using Machine Learning

Liver disorders constitute a major global health burden, with rising incidence due to lifestyle triggers such as alcohol consumption, metabolic disorders, viral infections, and medication toxicity. Ayurveda attributes the pathogenesis of most liver ailments—including Yakrit Vikara, Kamala, and Pandu—to vitiation of Pitta Dosha, which governs metabolism and biochemical transformation within the body. Traditional assessment of Pitta dominance relies on subjective Prakriti examination and clinical observation by Ayurvedic practitioners. With advances in artificial intelligence, machine learning offers the potential to extract objective patterns from physiological and clinical data to support diagnosis and prognosis. This research proposes an automated machine learning-based diagnostic framework to classify liver disorders based on Pitta dosha-related physiological attributes using structured clinical datasets. Feature selection, classification performance, and decision-support capabilities were evaluated using multiple ML algorithms, indicating that Random Forest and Support Vector Machine models provided superior accuracy. The results demonstrate the feasibility of integrating Ayurvedic Dosha concepts with machine learning for improved liver disorder prediction and personalized treatment planning.