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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.

Original publication

DOI

10.1017/pcm.2025.10006

Type

Journal article

Journal

Camb Prism Precis Med

Publication Date

2025

Volume

3

Keywords

artificial intelligence, breast cancer, cancer diagnosis, histopathology, neural networks