Abstract Paper

Title	: AI IN PULMONARY ONCOLOGY OPPORTUNITIES, RISKS, AND FUTURE DIRECTIONS
Author(s)	: T. Sudarshan, S Harini, S. Dayana and P. Amudhanila*
Article Information	: Volume 10 - Issue 01 (June - 2026) , 1239-1251
Affiliation(s)	: PG & Research Department of Microbiology, Sacred Heart College (Autonomous), Tirupattur - 635 601, Tamil Nadu, India.

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Abstract :

Artificial intelligence has the potential to revolutionize pulmonary oncology through improved diagnostic accuracy, personalized treatment strategies, and enhanced prognostic capabilities for lung cancer patients. Lung cancer remains the leading cause of cancer-related mortality worldwide, with non-small cell lung cancer accounting for approximately 85% of all cases. AI-based medical image analysis enables detection and characterization of early-stage lung cancer through radiomic analysis of computed tomography images. Artificial intelligence can integrate multi-omics approaches including genomics, transcriptomics, proteomics, and immunogenomics to advance precision oncology for lung cancer. However, several significant obstacles prevent widespread clinical adoption, including limited standardized AI training in medicine, insufficient external validation of models, and safety and ethical concerns regarding algorithmic transparency and data privacy. This paper critically evaluates the evolving role of AI technology in pulmonary oncology, examining current applications in diagnostic imaging, radiomics, genomics, transcriptomics, immuno-oncology, liquid biopsy, and pediatric oncology. We also discuss technical challenges including data quality, model interpretability, and validation requirements, and propose future directions emphasizing multicenter collaboration and explainable AI frameworks.

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Keywords	: Artificial Intelligence, Lung Cancer, Pulmonary Oncology, Diagnostic Imaging, Radiomics, Transcriptomics, Immuno-oncology, Liquid Biopsy, Precision Medicine
Document Type	: Research Paper
Publication date	: June 16, 2026

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