Artificial Intelligence in Oncology: Promise or Peril in Early Cancer Detection?

Artificial Intelligence (AI) is reshaping oncology by revolutionizing early cancer detection through advanced machine learning (ML) and deep learning (DL) techniques. These technologies analyze complex datasets—medical imaging, genomic profiles, electronic health records (EHRs), and liquid biopsies—with unprecedented precision, promising earlier diagnoses, improved survival rates, and reduced healthcare disparities. This comprehensive review synthesizes AI’s applications in imaging analysis, genomic profiling, risk prediction, and population screening, supported by a robust body of evidence from high-impact studies. We evaluate AI’s potential to enhance diagnostic accuracy, personalize medicine, and democratize healthcare access while critically addressing its challenges, including data biases, ethical dilemmas, regulatory complexities, and integration barriers. By exploring recent advancements, clinical trials, and emerging technologies, this review provides a balanced perspective on AI’s transformative promise and inherent perils in early cancer detection, emphasizing the need for rigorous validation, equitable implementation, and interdisciplinary collaboration to ensure its responsible adoption in clinical practice.

Keywords:

AI , early cancer detection , machine learning , deep learning , medical imaging , genomic profiling , risk prediction , healthcare disparities