Aarogyam UK  : A roundtable Summit with Aarogyam UK researchers and Association Ayurveda Academy Physicians to Develop AI based Computing Models for Indian Ayurveda

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Aarogyam UK 

INVC NEWS
New Delhi ,

Ayurveda Physician Researchers from Aarogyam UK working together with national and international experts in biomedical engineering and artificial intelligence-based models can establish scientific pieces of evidence on Ayurveda and Yoga-based healing practices in the UK.

Dr. Neha Sharma, a Leading researcher and healthcare expert from the UK, said the ML/ AI-based model created by the researchers in the UK earlier was based on data from more than mild to moderate COVID-19 patients treated by Ayurveda in the UK. The model was able to predict the efficacy of Ayurveda in COVID-19 treatment of mild to moderate cases. The protocol was based on the AYUSH-treatment protocol and executed by Aarogyam UK and the University of Warwick in 2020-2021.

Dr. D P Sharma, a Computer Scientist, and Digital Diplomat, while speaking said, Machine learning, Deep learning, Artificial Intelligence, and Big data analytics have become increasingly prominent in healthcare, as healthcare providers are increasingly using them to enhance the evidence bases. He added the comparative analytics of evidence-based intervention/ treatment of allopathy vs. Ayurveda will provide a new approach and support to Ayurveda at the global level.

Dr. Sharma said that data collected from the intervention of both allopathy and Ayurveda for similar diseases if analyzed by trained computing systems using Machine learning, Deep learning, or Few-shot learning, will provide a new pattern in scientific pieces of evidence with cross-validation. He further added that we are in a converged world, and Indian Yoga and Ayurveda can converge with other medication systems of the world but it needs valid data pieces of evidence that can be scaled up for analytics. Applying machine learning to Ayurveda-based intervention and modeling can establish a traditional healing mode on modern scientific measures.

Dr. Neha added that another study discussed at the roundtable was LONG-COVID, which has been a serious issue in the UK.

British Parliament is soon to discuss the serious concerns raised by Academics UK and ways to manage, said Dr. Madan, Genome Scientist, Cambridge University UK. He also added that Ayurveda-based texts and scripture could be a help.

The community support project in 2021 initiated by Aarogyam UK has been supporting Long COVID patients since then with Yoga and Ayurveda healing modalities. Dr. Neha Sharma discussed the potential of using practice-based data through different data science technologies which can show the potential of POST COVID with Ayurveda.

Another burdening issue in the UK is chronic pain conditions. A 12-step program for fibromyalgia and chronic fatigue syndrome of Aarogyam UK has worked on more than a thousand patients over the 6-months. Dr. Krithika Pandey, who is formalizing the first Ph.D. project in the UK on Ayurveda, discussed with Dr. DP Sharma the potential of secondary analysis and managing ethical concerns.

Aarogyam UK 
Aarogyam UK

Dr. Venkata Joshi added his recent experience from the Ayu-Psychiatry care project where Ayurveda was integrated into mental health, mainly emergency Psychiatry care in the India-UK partnership initiative. Data from 3 states to include as secondary analysis may provide details of potential benefits in emergency care.

D.P Sharma will be leading the Data analysis and AI team of researchers for Partnered network of Aarogyam (UK), Association Ayurveda Academy, and European Ayurveda Academy. Prabhu Shah (Aarogyam-Patanjali UK), Dr. Remya Nair (Aarogyam UK-Naturz UK), and Marine (European Ayurveda Academy) participated in a discussion to add on chronic illnesses, women’s health areas, and mental health diagnosis prospect.

Dr. Neha Sharma and Dr. Venkata Narayan Joshi initiated from the UK and catalyzed this global summit on exploring the converging benefits of data pieces of evidence, and technology in Ayurveda.

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