MUMBAI, India, June 30 -- Intellectual Property India has published a patent application (202641073933 A) filed by Keshav Memorial Institute Of Technology on June 15, 2026, for Cure Quest – A Machine Learning Based Early Disease Prediction System.
Inventors include Ms. Komal Bukka; Ms. Yasaswini Kotamraju; Ms. N Parimala; Ms. K Jamuna Rani; Ms. G Manjula; Ms. Baswari Richitha; Mr. Anuna Reddy; and Mr. Tunguturi Sriram Kalyan.
The application for the patent was published on June 26, 2026, under issue no. 26/2026.
Abstract: This project is a healthcare-focused web application built with Flask that combines Machine Learning, Deep Learning, and a medical AI chatbot to assist in early disease detection and patient support. It predicts Diabetes, Breast Cancer, Heart Disease, Kidney Disease, and Liver Disease using ML models trained on datasets from Kaggle and the UCI Repository, while Malaria and Pneumonia are detected through Convolutional Neural Networks applied to medical image datasets. The system integrates a conversational medical bot powered by AI to guide users, answer health-related queries, and provide basic recommendations alongside predictions. The backend is developed in Python with Flask, while the interface is designed using HTML, CSS, and Bootstrap for simplicity and ease of use. Core libraries such as Scikit-learn, TensorFlow/Keras, NumPy, Pandas, and Matplotlib are employed for data preprocessing, model training, and evaluation, with pre-trained models stored for efficient real-time predictions. The application achieves high accuracies, including ~98% for Diabetes and Breast Cancer, ~99% for kidney disease, ~96% for Malaria, and ~95% for Pneumonia. Users can either enter clinical data or upload medical images, receive instant diagnostic results, consult the medical chatbot for guidance, and even book appointments or connect with doctors through chat or email. Overall, the platform acts as an integrated solution that demonstrates multi- disease prediction, medical assistance through AI, and seamless web deployment, highlighting the potential of combining ML, DL, and conversational AI in healthcare
Disclaimer: Curated by HT Syndication.
