MUMBAI, India, May 29 -- Intellectual Property India has published a patent application (202641061685 A) filed by Christ University, Bengaluru, Karnataka, on May 15, for 'machine learning system for non-invasive pcos risk prediction and personalized recommendation.'
Inventor(s) include Dr. Sathya P; and Annu Punnoose.
The application for the patent was published on May 29, under issue no. 22/2026.
According to the abstract released by the Intellectual Property India: "The invention relates to digital health diagnostics and machine-learning based clinical decision support, and discloses a system and computer-implemented method for non-invasive prediction of PCOS risk using patient-reported data entered via a PCOS risk predictor interface. A data acquisition component receives values through structured input fields, including a cycle regularity selector, cycle length entry field, pregnancy status selector, abortion count selector, and symptom and lifestyle input group, which are validated by an input validation engine and transformed by a preprocessing layer into a machine-readable feature vector. A machine-learning prediction engine employing a trained ensemble classifier generates a PCOS risk output, after which a patient segmentation layer assigns a risk-linked and symptom-linked profile. A recommendation engine produces personalized advisory outputs, rendered through a prediction output interface or low-risk PCOS prediction output interface, together with feature-importance information and profile-specific guidance."
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