Classification of Ayurveda constitution types: a deep learning approach

In precision medicine, there has been a paradigm shift, from a population average based one-size-fits all, to an individualized approach. The aim is to tailor a medicine according to an individual’s genetic make-up and response to drug, diet, and environment. Machine learning algorithms are being developed to dissect inter-individual variability in the population. This is more important for prevention of diseases in healthy individuals and early actionable interventions. In Ayurveda, the basic tenet of the practice is personalized—an individual’s constitution type “ Prakriti ” is used for predicting healthy and disease trajectories as well as individualized management. Prakriti refers to the nature of the body in terms of doshas, and the time of conception is decided according to the predominance of doshas. It does not change throughout life and is responsible for a person’s physical and mental characteristics. Any population can be stratified into seven Prakriti groups amongst which the Vata , Pitta and Kapha are the three phenotypic extremes with contrasting disease susceptibilities and response. Prakriti is assessed through examination of multi-system attributes and has been formalized into a questionnaire that captures 120 feature attributes for objective assessment. We use for the first time—powerful dense neural network deep learning algorithms for predicting Prakriti classes. The study was carried out on a validated dataset of 233 extreme Prakriti individuals derived from two genetically diverse cohorts from North and West India. We benchmark our method with the state-of-the-art supervised machine learning and establish a learning approach for transferring features from the Western to Northern Indian data and vice versa as well. Our study provides a computational framework for predicting Prakriti which can be implemented in large scale studies of precision medicine. The dataset and the baseline implementation can be found in ( https://github.com/skarifahmed/DeepAyurveda )