MUMBAI, India, Feb. 13 -- Intellectual Property India has published a patent application (202641008428 A) filed by Sr University, Warangal, Telangana, on Jan. 28, for 'a knowledge-driven explainable ai method for early lung cancer detection and classification based on clinical attributes and tomographic imaging.'
Inventor(s) include Dr. G. Ashok Kumar; and Dr. Balajee Maram.
The application for the patent was published on Feb. 13, under issue no. 07/2026.
According to the abstract released by the Intellectual Property India: "A Knowledge-Driven Explainable AI Method for Early Lung Cancer Detection and Classification Based on Clinical Attributes and Tomographic Imaging 2.Abstract The present invention discloses a knowledge-driven explainable artificial intelligence method for early lung cancer detection and classification using a combination of clinical attributes and tomographic imaging data. The proposed method integrates domain knowledge derived from clinical guidelines and medical expertise with data-driven learning models to enhance diagnostic accuracy and interpretability. High-resolution tomographic images are analyzed alongside structured clinical attributes such as patient history, risk factors, and symptom profiles to identify early-stage lung cancer and classify disease subtypes. Explainability mechanisms provide transparent reasoning by highlighting relevant imaging regions and clinical features influencing each diagnostic outcome. The method supports clinician understanding, trust, and informed decision-making while facilitating early intervention. By aligning artificial intelligence predictions with established medical knowledge, the invention promotes reliable, accountable, and sustainable adoption of explainable AI in lung cancer diagnosis and classification. Keywords Early lung cancer detection, Explainable artificial intelligence, Knowledge-driven diagnosis, Tomographic imaging, Clinical attribute analysis, Lung cancer classification."
Disclaimer: Curated by HT Syndication.
