Ayurvedic Prakriti Classification Using Machine Learning: An IKS-Driven Approach to Personalized Healthcare

Ayurveda, one of the oldest traditional healthcare systems in India, emphasizes personalized medicine based on the concept of Prakriti, which represents an individual's natural constitution determined by the balance of three doshas: Vata, Pitta, and Kapha. Traditional methods of determining Prakriti involve clinical observation and assessment by experienced Ayurvedic practitioners. However, this process may be subjective and time-consuming. The integration of modern computational techniques such as machine learning provides an opportunity to standardize and automate this classification process. This study proposes a machine learning–based approach for identifying Ayurvedic Prakriti using questionnaire-based health and lifestyle data. The research follows an Indigenous Knowledge Systems (IKS) framework by combining traditional Ayurvedic concepts with modern data-driven methods. Various classification algorithms are applied to analyze the dataset and predict constitutional types. The results indicate that machine learning models can effectively support Prakriti classification and may contribute to the development of digital healthcare systems focused on preventive and personalized medicine.