Intellectual Property India Publishes Patent Application for Machine Learning-Based Dna Mutation Detection And Healthcare Decision Support System For Early Disease Prediction

MUMBAI, India, July 7 -- Intellectual Property India has published a patent application (202641073600 A) filed by Burra Venkata Sesha Talpa Sai; Swathi S; Kanakala Srinivas; Amshavalli M; Varikuti Triveni; Dr. B. Usharani; Dayananda Sagar Academy Of Technology And Management; Milind Chandrakant Tote; Ushasree R; Anvesh Perada; Mr. Arpan Debnath; and Dr. Tamilarasi Rajamani on June 13, 2026, for Machine Learning-Based Dna Mutation Detection And Healthcare Decision Support System For Early Disease Prediction.

Inventors include Burra Venkata Sesha Talpa Sai; Swathi S; Kanakala Srinivas; Amshavalli M; Varikuti Triveni; Dr. B. Usharani; Milind Chandrakant Tote; Ushasree R; Anvesh Perada; Mr. Arpan Debnath; and Dr. Tamilarasi Rajamani.

The application for the patent was published on July 03, 2026, under issue no. 27/2026.

Abstract: Machine Learning-Based DNA Mutation Detection and Healthcare Decision Support System for Early Disease Prediction is the proposed invention. The proposed invention is a machine learning-based DNA mutation detection and healthcare decision support system for early disease prediction is disclosed. The system integrates genomic sequencing technologies, cloud-connected healthcare infrastructure, and a Transformer-based deep learning architecture for intelligent genomic analysis and predictive healthcare management. DNA sequence data are pre-processed and analysed using self-attention mechanisms capable of identifying pathogenic mutations, nucleotide dependencies, and disease-associated genomic patterns. The system predicts susceptibility to hereditary, oncological, neurological, cardiovascular, and metabolic disorders while generating personalized clinical decision support recommendations including diagnostic insights, risk assessment scores, and preventive healthcare strategies. The invention enables accurate mutation detection, improved disease prediction, adaptive learning-based healthcare analytics, and scalable precision medicine support for advanced medical applications.

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