0.99 CME

Role of AI in Diabetes Care & Metabolic Wellness

Speaker: Dr. Rohit Warrier

Senior Diabetes Specialist & physician, Apollo & Apotek Healthcare, Global Teaching faculty, American Board of Regenerative Medicine

Description

AI is increasingly playing a significant role in diabetes care and metabolic wellness by enhancing early detection, personalized treatment, and continuous monitoring. Machine learning algorithms analyze patient data, such as glucose levels and lifestyle factors, to provide more accurate predictions and tailored management plans. AI-powered tools, like smart insulin pumps and continuous glucose monitors, help patients track their condition in real time, improving outcomes and reducing complications. Additionally, AI assists healthcare providers in identifying trends, optimizing treatment strategies, and enabling more proactive care for individuals with diabetes or metabolic disorders.

Summary

The speaker introduces the technology of AI, specifically focusing on digital twin models. The digital twin model was first used by NASA to speculate possible errors during rocket launches, and has played a revolutionary role in autonomous driving cars and space science. In healthcare, Twin Health is mapping this principle to build a digital twin model of patients, aiming to bring about metabolic wellness.
The speaker explains that the program is fundamentally a metabolic wellness program that aims to look into the root cause of metabolic problems. The root cause of these conditions must be looked into in order to provide a long-lasting solution, as the metabolic picture is very unique for every single patient. A digital twin model can help heal a damaged metabolic picture that contributes to these conditions.
RCT data has shown remarkable improvement in terms of remission of type 2 diabetes, as well as improvements in high blood pressure, dyslipidemia parameters, obesity normalization, ASVD scores, kidney health, fatty liver scores, pancreatic health, high inflammation, and insulin resistance. This is the power of AI in digital twins to heal damaged metabolism through a correction plan. The digital twin knows exactly what each person requires to heal their damaged metabolic picture.
The speaker explains that live data is needed to build a digital twin, which comes from sensor data, lab work, and data patients enter into the technology. An AI system learns by itself through an autonomous unsupervised learning algorithm, which allows the system to learn from the data of many patients. The AI system then gives precision guidance regarding nutrition, medication, sleep, and activity.
The technology's precision in diet recommendations is highlighted. It considers micronutrients (omega-3 fatty acid, tryptophan, fructose, sodium, potassium, zinc) rather than solely macronutrients (proteins, carbohydrates, and fat). The recommendation helps restore a good, healthy bacteria in the gut. Over time, by following the recommendations, the body can return back to health.
The speaker emphasizes that data integrity and ethical standards are crucial in managing AI in managing diabetes. There must be multiple layers of security to prevent data breaches and data privacy must be protected. HIPPA compliance is a must to ensure patient data protection.