• ShripadGurunathrao Kulkarni
• Dr. Nagnath Hulle

For ages, traditional medicine professionals have utilized the appearance of the tongue as a diagnostic tool. Change in color, texture, and layer can show different health problems. Recent study is bringing this old practice into the 21st century by using advanced computer techniques, especially machine learning, to analyze the human tongue digitally. The tongue is easy to see and can show a lot about the body's overall health. Small changes can happen before or along with more obvious signs of illness. This is a good option for finding issues early and preventing problems. However, these changes can be tricky to understand and often vary from person to person. This is where artificial intelligence plays a role. Researchers have found that standard machine learning models are useful, but they can be improved. Reinforced learning (RL) is a method where AI agents learn by trying things out and getting benefits or punishments based on how right they are. This approach could lead to a more flexible and accurate tool for diagnosing problems. Think of a system where an AI learns from a large collection of tongue pictures linked to different health issues. It keeps improving itself through a method called reinforced learning. The method begins by looking at an image. It suggests a diagnosis based on the first study. Medical experts review this exam and give feedback by rewarding correct answers and penalizing wrong ones. This "feedback loop" helps the AI model keep learning and getting better at making accurate diagnoses.

Tongue, Health Monitoring, Reinforced Learning, Machine Learning, Tongue color, Tongue Texture

"Tongue based Health Monitoring using Reinforced Machine Learning: A Study", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 8, page no.165-176, August-2025, Available :http://www.jetir.org/papers/JETIRHA06024.pdf

"Tongue based Health Monitoring using Reinforced Machine Learning: A Study", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 8, page no. pp165-176, August-2025, Available at : http://www.jetir.org/papers/JETIRHA06024.pdf