MUMBAI, India, June 26 -- Intellectual Property India has published a patent application (202641036712 A) filed by Rmk Engineering College on March 26, 2026, for A Reinforcement Learning Driven Personalized Treatment Recommendation System With Encrypted Decision Traceability Mechanism.
Inventors include E. Thenmozhi; B. Saratha; R. Devi; B. Mythili; Dr. G. Manikandan; Dr. B. Muthazhagan; and E. Sathesh Abraham Leo.
The application for the patent was published on June 19, 2026, under issue no. 25/2026.
Abstract: The present invention relates to an intelligent healthcare decision support system titled “A Reinforcement Learning Driven Personalized Treatment Recommendation System with Encrypted Decision Traceability Mechanism.” The system is designed to assist healthcare professionals in generating optimized and personalized treatment recommendations using advanced artificial intelligence techniques. The proposed system collects patient medical data from multiple healthcare sources including electronic health records, diagnostic reports, laboratory results, wearable health devices, and clinical databases. The collected data is processed through a data preprocessing and feature extraction module that converts heterogeneous medical information into structured datasets suitable for machine learning analysis. A reinforcement learning engine analyzes patient health conditions, historical treatment records, and clinical outcomes to determine the most effective treatment strategy for each individual patient. The system continuously learns from treatment outcomes and updates its decision policies in order to improve long-term clinical effectiveness and patient recovery rates. In addition, the invention incorporates an encrypted decision traceability mechanism that securely records the reasoning process behind each treatment recommendation. The decision logs are encrypted and stored in a secure storage framework to ensure transparency, integrity, and accountability of AI-based medical decisions. The proposed system enhances personalized healthcare delivery, supports clinicians in evidence-based treatment planning, and ensures secure and traceable artificial intelligence assisted medical decision making. Keywords Reinforcement Learning, Personalized Treatment Recommendation, Clinical Decision Support System, Encrypted Decision Traceability, Healthcare Artificial Intelligence.
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