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VOL. 8, ISSUE 1 (2026)
The role of Artificial Intelligence in the detection of breast cancer: A narrative review
Authors
Dr. Nishant Mishra, Dr. Sanskriti Shukla, Dr. Rahul Tanwar, Dr. Jyotsna Sen
Abstract
Background: Breast cancer is one of the most common malignancies among women
worldwide, and early detection remains critical for improving survival and
treatment outcomes. Conventional imaging-based screening methods are limited by
inter-observer variability and increasing workload demands.
Objective: To review the role of artificial intelligence (AI) in the detection of breast cancer, with emphasis on imaging applications, diagnostic performance, and clinical integration.
Materials and Methods: A narrative review of the literature published between 2015 and 2024 was conducted using electronic databases including PubMed, Google Scholar, and Scopus. Studies evaluating AI-based applications in mammography, breast ultrasound, and breast MRI were reviewed. Original research articles, validation studies, and systematic reviews were included, while case reports and non-peer-reviewed articles were excluded.
Results: AI-based systems demonstrated high diagnostic performance across breast imaging modalities, with reported sensitivities ranging from approximately 85% to over 94% in selected studies. AI-assisted workflows showed improved lesion detection, reduced false-positive rates, and enhanced radiologist efficiency, particularly when used as a decision-support tool rather than as a standalone system.
Conclusion: Artificial intelligence has significant potential to augment breast cancer detection and screening by improving diagnostic accuracy and workflow efficiency. However, challenges related to generalizability, interpretability, and regulatory implementation must be addressed before widespread clinical adoption.
Objective: To review the role of artificial intelligence (AI) in the detection of breast cancer, with emphasis on imaging applications, diagnostic performance, and clinical integration.
Materials and Methods: A narrative review of the literature published between 2015 and 2024 was conducted using electronic databases including PubMed, Google Scholar, and Scopus. Studies evaluating AI-based applications in mammography, breast ultrasound, and breast MRI were reviewed. Original research articles, validation studies, and systematic reviews were included, while case reports and non-peer-reviewed articles were excluded.
Results: AI-based systems demonstrated high diagnostic performance across breast imaging modalities, with reported sensitivities ranging from approximately 85% to over 94% in selected studies. AI-assisted workflows showed improved lesion detection, reduced false-positive rates, and enhanced radiologist efficiency, particularly when used as a decision-support tool rather than as a standalone system.
Conclusion: Artificial intelligence has significant potential to augment breast cancer detection and screening by improving diagnostic accuracy and workflow efficiency. However, challenges related to generalizability, interpretability, and regulatory implementation must be addressed before widespread clinical adoption.
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Pages:5-6
How to cite this article:
Dr. Nishant Mishra, Dr. Sanskriti Shukla, Dr. Rahul Tanwar, Dr. Jyotsna Sen "The role of Artificial Intelligence in the detection of breast cancer: A narrative review". International Journal of Radiology Research, Vol 8, Issue 1, 2026, Pages 5-6
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