MUMBAI, India, May 1 -- Intellectual Property India has published a patent application (202611025662 A) filed by Swami Vivekanand Subharti University, Meerut, Uttar Pradesh, on March 4, for 'a method and a system for optimized antifungal therapy selection based on severity grading and recurrence risk prediction.'
Inventor(s) include Neelam; and Dr. Mukesh Kumar.
The application for the patent was published on May 1, under issue no. 18/2026.
According to the abstract released by the Intellectual Property India: "The present disclosure relates to a system and method for optimized antifungal therapy selection based on automated severity grading and recurrence risk prediction. The system integrates clinical data acquisition, artificial intelligence (AI), and machine learning (ML) techniques to analyze multidimensional dermatological and mycological parameters including lesion morphology, inflammation indices, laboratory findings, prior antifungal exposure, and treatment adherence history. A predictive modeling engine generates a standardized severity grade and a quantitative recurrence risk index using trained algorithms. Based on these outputs, a therapy recommendation unit dynamically correlates infection severity and relapse probability with predefined therapeutic optimization matrices to generate risk-stratified antifungal treatment advisories, including drug selection, dosage strength, duration, and follow-up scheduling. The system may further employ federated learning for continuous model refinement while preserving patient privacy."
Disclaimer: Curated by HT Syndication.
