Revolutionizing Early Cancer Diagnosis Using Artificial Intelligence

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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