Swasthavritta in Contemporary Healthcare: Bridging Ayurveda Preventive Medicine with Artificial Intelligence–Enabled Advancements
DOI:
https://doi.org/10.47070/ayushdhara.v13i4.2921Keywords:
Swasthavritta, Ayurveda, Preventive medicine, Dinacharya, Artificial intelligence, Digital health, Non-communicable diseases, PrakritiAbstract
Swasthavritta, one of the eight classical branches of Ayurveda (Ashtanga Ayurveda), is the discipline devoted exclusively to preserving health in the healthy and preventing disease through daily regimen (Dinacharya), seasonal regimen (Ritucharya), ethical conduct (Sadvritta) and dietary discipline (Ahara-Vihara). As the global burden of non-communicable diseases (NCDs) continues to rise, and as Artificial Intelligence (AI) increasingly permeates healthcare, there is renewed interest in re-examining Swasthavritta through a contemporary, technology-enabled lens. Objective: To review the conceptual and scientific basis of Swasthavritta, appraise its relevance to present-day preventive healthcare, and critically synthesize emerging artificial-intelligence-enabled advancements supporting its practice. Methods: A narrative literature search was performed across PubMed/MEDLINE, Google Scholar, ScienceDirect and the AYUSH Research Portal. Classical Ayurveda texts and peer-reviewed reviews, original studies, and policy documents published predominantly between 2015 and 2026 were prioritized. Discussion: Dinacharya and Ritucharya show conceptual and partial mechanistic overlap with chronobiology and chrono nutrition, and have been proposed as a quaternary-prevention strategy against NCDs. Machine-learning models can classify Prakriti constitutional types from phenotypic data with high accuracy, sensor-based Nadi Pariksha devices are being explored for objective pulse diagnosis, and national digital-health infrastructure is scaling Ayurveda preventive services. Conclusion: Swasthavritta offers a systematized, low-cost preventive framework with renewed relevance to the modern NCD epidemic. Artificial intelligence holds promise for standardizing, personalizing and scaling its application, provided larger prospective trials, harmonized data standards and ethically governed technology co-design accompany its adoption.
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