Decoding Prakriti through Computer Vision and AIOT
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Convenors: Dr. Saketh Thirugulla and Dr. Sumit Kalra
Team members – Dr. Renu Singh, Dr. Bharat Kumar Padhar, Dr. Shweta Telang Chaudhari, Dr. Dinesh Chandra Sharma, Dr. Pranjal Protim Borah, Dr. Rajendra Nagar, Dr. Mona Duggal
Volunteers – Dr. Deepika Jangir, Dr. Manish Yadav
Key Pointers :
How does transitioning Prakriti to an objective digital metric remove subjective bias and create a "common language" for both Ayurvedic practitioners and modern clinicians?
In what ways do these digital phenotyping tools act as assistive technologies to establish a baseline of health that is recognized by both systems?
How does ontology engineering specifically enable "seamless cross-talk" between traditional constitutional assessments and modern medical diagnostics?
This session will focus on the operationalization of Prakriti, transitioning it from traditional clinical observation to a high-precision digital metric. By leveraging the latest in Capture Technologies, Digital Health, and AIOT, we move toward an AI enabled objective assignment of Prakriti through digital health platforms.
Key Discussion Points:
Baselines of health through the lens of Prakriti: An exploration of the nuances and determinants that define individual health baselines.
Prakriti underpinnings in disease and intervention: Understanding how constitutional types influence disease progression and the efficacy of personalized interventions.
Computer Vision and Capture Technologies: Utilizing AI-assisted computer vision and AIOT to provide objective Prakriti assignments, removing subjective bias.
Integration with the PRISM Platform: Demonstrating how these digital phenotyping tools serve as assistive technologies to create Prakriti-Informed Digital Twins.
Evidence-Based Solutions: Discussing how digital phenomics facilitates seamless cross-talk between Ayurveda and modern medicine through ontology engineering.
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