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Research and review articles are invited for publication in September 2026 - Vol. 36, Issue 3 

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Artificial Intelligence for lung cancer diagnosis and treatment: A comprehensive review

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  • Artificial Intelligence For Lung Cancer Diagnosis and Treatment: A Comprehensive Review
  • Artificial Intelligence for lung cancer diagnosis and treatment: A comprehensive review

Kuldip K. Badukale *, Pooja R. Hatwar and Ravindra L. Bakal

Shri Swami Samarth Institute of Pharmacy, At Parsodi, Dhamangaon Rly, Dist Amravati (444709), Maharashtra, India.
Research Article
GSC Biological and Pharmaceutical Sciences, 2025, 33(03), 271–281.
Article DOI: 10.30574/gscbps.2025.33.3.0516
DOI url: https://doi.org/10.30574/gscbps.2025.33.3.0516
Received on 15 November 2025; revised on 20 December 2025; accepted on 23 December 2025
Lung cancer is a leading cause of cancer-related deaths worldwide. Artificial intelligence (AI) has emerged as a transformative force in modern healthcare, revolutionizing diagnostic accuracy, treatment efficacy, and patient management. This review aims to investigate the current state of AI and machine learning applications in lung cancer care, focusing on critical studies, achievements, and future directions. AI technologies, such as machine learning and deep learning, have shown promise in improving lung cancer diagnosis, predicting treatment outcomes, and enhancing patient care. The benefits of AI in healthcare, including personalized recommendations, improved diagnostic accuracy, and enhanced patient outcomes. Also explore the applications of AI in lung cancer, including image analysis, risk prediction, and treatment planning.
Artificial Intelligence; Lung Cancer; Machine Learning; Deep Learning; Diagnosis; Treatment
https://gscbps.gsconlinepress.com/sites/default/files/fulltext_pdf/GSCBPS-2025-…

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Kuldip K. Badukale, Pooja R. Hatwar and Ravindra L. Bakal. Artificial Intelligence for lung cancer diagnosis and treatment: A comprehensive review. GSC Biological and Pharmaceutical Sciences, 2025, 33(3), 271-281. Article DOI: https://doi.org/10.30574/gscbps.2025.33.3.0516


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