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Revolutionizing Early Cancer Diagnosis Using Artificial Intelligence: A Systematic Review
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Author(s): Tariq Saeed Mian (Taibah University, Saudi Arabia), Hisham Farooq Saeed (Fatima Medical and Saleem Surgical Hospital, Sheikhupura, Pakistan)and Eman M. Alatawi (Taibah University, Saudi Arabia)
Copyright: 2026
Pages: 30
Source title:
AI and Machine Learning for Cancer Care: Precision Medicine and Beyond
Source Author(s)/Editor(s): Manvi Mishra (Shri Ram Murti Smarak College of Engineering and Technology, Bareilly, India), Piyush Kumar (Shri Ram Murti Smarak Institute of Medical Sciences, Bareilly, India), Himanshi Khattar (Shri Ram Murti Smarak Institute of Medical Sciences, Bareilly, India)and Mohammad Zubair Khan (Islamic University of Madinah, Saudi Arabia)
DOI: 10.4018/979-8-3373-4312-9.ch003
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Abstract
Early cancer diagnosis significantly improves treatment outcomes and survival rates. While traditional diagnostic methods face challenges in accuracy, speed, and accessibility, artificial intelligence (AI) offers transformative solutions. AI models, particularly machine learning (ML) and deep learning (DL), excel at learning complex data patterns to predict early-stage cancer, enhancing existing diagnostics. This review examines the scope of AI in early cancer detection, analysing studies categorised by cancer type, diagnostic modality, AI methodology, and performance. AI consistently demonstrates superior sensitivity and specificity compared to conventional methods, especially in radiology, pathology, and genomics. Despite promising advancements, further exploration and collaborative efforts between clinicians, researchers, and technologists are crucial to address limitations and ensure effective clinical implementation.
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