Leveraging Artificial Intelligence as a Tool to improve health services and Modernize Ayurveda Treatment – A perspective

Abstract

Artificial Intelligence aids in making robots, Bots, and other machines meant for specific tasks. Through self-learning, machines today can enhance their intelligence to a smarter level. This technology can be harnessed to better the lives of the underprivileged, the marginalized, and the needy. In that programme on Artificial Intelligence, I urged the scientific community to deliberate on how Artificial Intelligence could help us make life easier for our divyang brothers & sisters. Can we make better predictions of natural disasters using Artificial Intelligence? Can we use it to provide assistance to farmers on crop yield? Can Artificial Intelligence be used as a tool to simplify the outreach of health services and modernize medical treatment? Hon’ble Prime Minister of India Shri Narendra Modi Mann Ki Baat - 25 Feb, 2018 In the 41st episode of Mann Ki Baat, the Hon’ble Prime Minister raised the question - Can Artificial Intelligence (AI) be used as a tool to simplify the outreach of health services and modernize medical treatment? Ayurveda is a health science, and the question of how AI can be helpful in Ayurveda is relevant. AI is the simulation of the process of human intelligence by computers. It deals with perceiving the environment, solving problems, and acting to achieve a specific goal[1]. John McCarthy is the father of AI, with his extensive experience in computers since he coined the term AI[2]. The deployment of AI in the medical field is growing. A recent review on AI published in Complementary and Alternative Medicine (CAM) analyzed Pubmed, Embase, and Cochrane databases to find studies on AI in CAM. AI was used in diverse fields, such as acupressure treatment, tongue and lip diagnosis, herbal medicines, pulse diagnosis, and TCM syndromes[3]. Another study has reported how thousands of images of Diabetic Retinopathy (DR) were used for training to achieve DR diagnosis with sensitivity and specificity[4]. Furthermore, there has been more and more AI integration happening in the conventional medical field, and so is introduction of AI in complementary and alternative medicine (CAM) is also being attempted[5] AI has potential to transform ancient science of Ayurveda. Opportunities for interdisciplinary research that joins AI and Ayurveda knowledge base can have breakthrough outcomes in terms of the prediction & prevention of diseases and in delivering personalized therapy. The Trisutra (three fundamental databases) of AI for Ayurveda are human data, Ayurveda therapeutics data, and disease data [Figure 1]. The first dataset on humans includes Dosha Prakriti (Somatic constitution) and its characteristics, Sapta Dhatu (major structural components of the body), 13 types of Agni (digestive/metabolic factors), 13 Srotas (structural or functional body channels), 3 Mala (Body waste products), and Oja (the essence of all seven Dhatu). The second set of Ayurveda therapeutics includes medicinal plants with their Rasa (taste), Guna (property/ quality/ attribute), Virya (Potency), Vipaka (bio-transformed rasa), and procedures like Panchakarma (five internal bio-cleansing therapies) as well as Pathyapathya (compatible diet & regimen). Lastly are the disease symptoms. These three datasets, or Trisutra for AI in Ayurveda, could be brought together to diagnose, predict, and prevent disease through drugs, diet, Dinacharya (daily regimen), and Ritucharya (seasonal regimens) concepts taking care of chronobiology.Fig. 1: Trisutra for AI in AyurvedaData and AI One of the early examples of a “Decision Support System” in Ayurveda was developed by CDAC Pune, where Ayusoft software was developed for Prakriti diagnosis[6]. Prakriti determines physical and mental characteristics important in deciding a therapeutic regime in Ayurveda. AI can be used to generate intelligent data from Prakriti assessment and fine-tuned for global use. Additionally, Genomic Biomarkers must be added to confirm Prakriti objectively[7,8]. Several predictions on drugs