MUMBAI, India, July 7 -- Intellectual Property India has published a patent application (202641081067 A) filed by Malla Reddy Engineering College Women Autonomous; Malla Reddy University; and Malla Reddy Mr Deemed To Be on July 01, 2026, for Disease Prediction Via Tongue Colour Analysis In Tcm Using Deep Learning.
Inventors include Dr. Y. Madhaveelatha; Dr. Pradeep Venuthurumilli; Dr. Devi Uma Moka; Mr. Prathap Songa; Ms Usha Rapaka; Dr. Ravi Rushan Kumar Chaudhary; Mr. Syed Abdul Haq; and Mr. M Ajaykumar.
The application for the patent was published on July 03, 2026, under issue no. 27/2026.
Abstract: Advancements in artificial intelligence and medical image analysis have significantly transformed modern healthcare systems by enabling automated, accurate, and efficient diagnostic solutions. Among various diagnostic approaches, non-invasive medical analysis techniques are gaining increasing importance because they reduce patient discomfort and enable early detection of potential health issues. One such traditional diagnostic method is tongue diagnosis, which has been widely used in Traditional Chinese Medicine (TCM) for centuries to assess a person's health condition by observing the color, texture, and coating of the tongue. However, conventional tongue diagnosis relies heavily on the experience and subjective interpretation of medical practitioners, which can lead to inconsistencies and variability in diagnosis. With the rapid development of deep learning and computer vision technologies, it has become possible to automate image-based diagnostic processes and improve their reliability and efficiency. Deep learning models, particularly Convolutional Neural Networks (CNNs), have demonstrated remarkable performance in medical image classification and pattern recognition tasks. By applying these techniques to tongue image analysis, it is possible to extract meaningful features from tongue images and identify patterns associated with different health conditions. The proposed system introduces an intelligent framework for disease prediction through automated tongue color analysis using deep learning techniques. The system utilizes advanced image processing methods and a hybrid machine learning architecture to analyze tongue images and classify them into different color categories associated with potential health conditions. The framework integrates a CNN-based feature extraction mechanism with a Random Forest classifier to enhance prediction accuracy and robustness.
Disclaimer: Curated by HT Syndication.
