MUMBAI, India, Jan. 9 -- Intellectual Property India has published a patent application (202541134111 A) filed by Meenakshi Academy Of Higher Education And Research, Chennai, Tamil Nadu, on Dec. 31, 2025, for 'system and method for clinical data mining and disease trend forecasting.'
Inventor(s) include Sakthivel M; Victor Devasirvadam; Selva Kumar; and Srimathi N.
The application for the patent was published on Jan. 9, under issue no. 02/2026.
According to the abstract released by the Intellectual Property India: "System and Method for Clinical Data Mining and Disease Trend Forecasting The present disclosure relates to a system and method that can forecast disease trends through clinical data mining and define how clinical data is processed, assessed and then used in a predictive computation. This system gathers clinical data from several sources, including healthcare providers and monitoring systems and validates that the data has integrity and provenance before it is processed in a way that will exclude data that does not have integrity or provenance from being used for prediction computation purposes. Validated clinical data is used to construct a set of disease -specific physiological representations that are analyzed based upon the relationships that exist between the cause and effect (C&E) of disease progression that have been validated through C&M and authoritative literature and are also governed based upon causality. Once validated C&E Relationships have been developed and established, the system is able to produce multi-scale temporal models of a disease trajectory, and regulate the resultant forecasts by computing and applying a series of confidence-index values that indicate the statistical reliability of the forecasts produced for each model. Forecasts of disease trends are generated only after pre-defined conditions for provenance, causality and confidence have all been met and are associated with audit-ready, explainable metadata by design. As a result of the application of a causality-based computation methodology, confidence-regulated forecasting methodology, and providing audit-ready traceability of all clinical data, this system and method represents a significant advancement over existing analytical methods that rely solely on a correlation basis."
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