Predicting Human Body Prakriti with Ayurvedic Tridosha Features using Ensemble Learning Models

Ayurveda, an ancient medical system, provides insight into personal health through the concept of Prakriti, which determines a person's constitution. Integrating these traditional concepts with modern medical practice is a huge challenge. The research has addressed this problem by developing a machine learning-based Prakriti estimation method. Advanced algorithms, including random forests and ensemble models, were used to analyze a rich dataset of biological traits not easily altered by current cosmetic or technological interventions. This approach achieved a remarkable accuracy of 98\%, validating the effectiveness of integrating machine learning and Ayurvedic principles. Future research will focus on expanding the dataset to include a wider range of biological features and improving feature selection methods to increase the generalizability and applicability of the model in various clinical settings, thereby improving the relationship between traditional Ayurvedic knowledge and modern medical practice. The gap must be narrowed further.