MUMBAI, India, Sept. 22 -- Intellectual Property India has published a patent application (202611091684 A) filed by Dr. Dina Hussein Hatif Al Mansoori; Dr. Firas Shawkat Al Bayati; Dr. Parthasarathi Murugesan; Dr. Vijayasamundeeswari. P; Subhasis Mohapatra; and Mrs. H. A. Bhavithra on July 28, 2026, for A System And Method For Intelligent Biological Data Analysis And Predictive Assessment.
Inventors include Dr. Dina Hussein Hatif Al Mansoori; Dr. Firas Shawkat Al Bayati; Dr. Parthasarathi Murugesan; Dr. Vijayasamundeeswari. P; Subhasis Mohapatra; and Mrs. H. A. Bhavithra.
The application for the patent was published on September 18, 2026, under issue no. 38/2026.
Abstract: The present invention relates to an intelligent biological data analysis and predictive assessment system and method. The system includes a biological data acquisition module configured to acquire heterogeneous biological information from laboratory instruments, sequencing platforms, biomedical sensors, imaging systems, environmental sensors and biological repositories. An adaptive biological data validation module is used to validate data quality and biological consistency and a biological data harmonization module is used to standardize heterogeneous datasets into a unified analytical representation. A biological feature extraction module extracts multi-level biological relevant features, and a biological knowledge relationship module constructs adaptive evidence-based biological relationships. A module for evidence validation validates biological consistency . A module for uncertainty quantification quantifies confidence in prediction . The predictive assessment module produces biological predictions and the explainable biological reasoning module detects biological factors that contribute to each prediction. When confidence is not high enough, an experiment recommendation module suggests additional biological investigations. The adaptive learning module continuously improves predictive performance with validated biological evidence, and a secure traceability module maintains complete processing records, thereby improving prediction reliability, analytical consistency, computational efficiency, and biological decision support. In additional embodiments, the system generates a Predictive Confidence Index, applies a confidence based prediction action matrix, decomposes predictive uncertainty into defined uncertainty components, applies a biological plausibility gate, maintains instrument and protocol normalization profiles, ranks additional investigations according to expected confidence gain, stores a prediction traceability fingerprint, and detects biological or measurement drift for recalibration, thereby improving reliability, reproducibility, and technical control of biological predictive assessments.
Disclaimer: Curated by HT Syndication.
