According to the United Nations Population Fund’s ‘India Ageing Report 2023’, the total number of elderly populations in the country is expected to double by 2050, accounting for 20.8 per cent of the total population. It also indicates a surge in age-related health challenges within this ageing demographic, calling for a special focus on more robust healthcare systems. One of the key ways to make the Medicare segment smarter, faster, and more efficient is by utilising modern technological tools like Artificial Intelligence (AI), Machine Learning (ML), and the Internet of Things (IoT). These groundbreaking technologies are already transforming the way we diagnose, treat, and monitor patients, especially those requiring geriatric care. Other than increasing the healthcare sector’s capability to analyse vast amounts of clinical data more efficiently, AI and ML algorithms are also aiding in the research and development of new methodologies by integrating traditional medical practices with allopathy, leading to groundbreaking initiatives.
The growing popularity of new methods like Polyscientific Ayurveda (PSA), which blends Ayurvedic practices with modern medicine and technology, elucidates this point. “The Polyscientific Ayurvedic method stands out as a pioneering integration of Ayurveda and Allopathy, characterized by its rigorously scientific approach to experimentation. We are likely unique globally in our development of animal models specifically for Vata, Pitta, and Kapha. These models are foundational to our mathematical modelling of these doshas. To my knowledge, no other entity worldwide has undertaken such an endeavor. This innovative work has enabled us to create reliable mathematical equations and algorithms, allowing for the quantification of Vata, Pitta, Kapha, and their sub-doshas, thereby bridging a critical knowledge gap between these two distinct medical disciplines.
His research correlates the Ayurvedic principles of doshas with various physiological and biochemical pathways in the body. “We have linked the three doshas and their five subtypes to specific frequency domains in heart rate variability and pulse pressure curves. With the help of these correlations, we have developed innovative machine-learning algorithms leading to the creation of an AIoT-driven platform. This platform is the foundation of our DOCTURE-POLY™️ device, which provides personalised, all-natural treatment remedies tailored to individual needs,” explains Dr Polisetty.
There are disparities in diabetes diagnosis standards among various associations, highlighting conflicting HbA1c levels set by the American Endocrine Knowledge Association, American Diabetic Association, and American College of Physicians. It introduces VPK 42 fingerprinting as a revolutionary tool that personalizes healthcare by identifying metabolic types and pathways unique to each individual. This approach allows for tailored dietary and fitness recommendations based on one’s specific metabolic needs. Particularly in diabetes management, understanding the unique metabolic demands of systems where Vata, Pitta, and Kapha are imbalanced is crucial. This personalized insight provided by VPK 42 fingerprinting is essential for effectively treating diabetes and can be extended to other diseases, offering a customized approach to healthcare.
According to him, to create a strong and forward-thinking healthcare infrastructure, India can focus more on improving healthcare facilities, increasing access to quality care and leveraging modern technology to integrate traditional and modern medical practices. “By promoting further research, education, and innovation, we can enhance our healthcare system and position India as a global leader in medical excellence. With concerted efforts and strategic investments, this vision is achievable in the coming decades,” concludes Dr Polisetty.
