Artificial intelligence in breast cancer diagnosis: A systematic literature review

Journal article : Review

Breast cancer is the second leading cause of cancer-related deaths among women globally and the most prevalent cancer in women. Artificial intelligence (AI)-based frameworks have shown great promise in correctly classifying breast carcinomas, particularly those that may have been difficult to discern through routine microscopy. Additionally, mitotic number quantification utilizing AI technology is more accurate than manual counting. With its many advantages, such as improved accuracy, efficiency and consistency as shown in this literature review, AI has promise for significantly enhancing breast cancer diagnosis in the clinical world despite the paramount obstacles that must be addressed. Ongoing research and innovation are essential for overcoming these challenges and effectively harnessing AI’s transformative potential in breast cancer detection and assessment.

Authors: Javaeed, A; Schuh, A

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Cambridge University Press
• Journal: Cambridge Prisms: Precision Medicine
• Volume: 3
• Pages: 1-48
• Article number: e7
• Publication date: 2025-11-21
• Acceptance date: 2025-11-09
• DOI: 10.1017/pcm.2025.10006
• EISSN: 2752-6143
• ISSN: 2752-6143
• Language: English
• Keywords: neural networks; cancer diagnosis; artificial intelligence; breast cancer; histopathology
• Subtype: Review