Artificial Intelligence in Breast Cancer Diagnosis and Management

Artificial intelligence (AI) holds significant promise in the fields of diagnostics and therapeutics, particularly in cancer management. AI has been extensively applied in various aspects of breast cancer care. Numerous studies and reviews have been published on the use of AI in breast cancer; however, many studies have focused on a single application and can be difficult to understand because of the complex nature of the jargon. This review aimed to comprehensively explore the various applications of AI in breast cancer management. AI has proven to be a valuable tool for enhancing the workflows of radiologists, pathologists, and clinicians. Although it has not yet replaced clinical decision-making, AI shows promising potential in molecular pathology, with the hope of advancing virtual biopsies. Progress in AI could also open new avenues for preventive oncology. Current clinical challenges in therapeutic practice can be addressed by utilising radiomics, which combines the clinical, imaging, and molecular characteristics of tumours to guide treatment decisions and target therapies more effectively. The potential of AI to improve patient outcomes, reduce workforce demand, and minimise postoperative complications suggests a promising future for its application in cancer care.

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Publication Details

Journal
British Journal of Hospital Medicine
Published
2025-12-19
DOI
https://doi.org/10.12968/hmed.2024.0786
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
0.00
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article

Artificial Intelligence in Breast Cancer Diagnosis and Management

Raghavan Vidya, Smitha S. Rao
British Journal of Hospital Medicine
Radiomics and Machine Learning in Medical Imaging
article

Artificial Intelligence in Breast Cancer Diagnosis and Management

Raghavan Vidya, Smitha S. Rao
article en

Abstract

Artificial intelligence (AI) holds significant promise in the fields of diagnostics and therapeutics, particularly in cancer management. AI has been extensively applied in various aspects of breast cancer care. Numerous studies and reviews have been published on the use of AI in breast cancer; however, many studies have focused on a single application and can be difficult to understand because of the complex nature of the jargon. This review aimed to comprehensively explore the various applications of AI in breast cancer management. AI has proven to be a valuable tool for enhancing the workflows of radiologists, pathologists, and clinicians. Although it has not yet replaced clinical decision-making, AI shows promising potential in molecular pathology, with the hope of advancing virtual biopsies. Progress in AI could also open new avenues for preventive oncology. Current clinical challenges in therapeutic practice can be addressed by utilising radiomics, which combines the clinical, imaging, and molecular characteristics of tumours to guide treatment decisions and target therapies more effectively. The potential of AI to improve patient outcomes, reduce workforce demand, and minimise postoperative complications suggests a promising future for its application in cancer care.

British Journal of Hospital MedicineVol. 86(12)
The Royal Wolverhampton NHS Trust (GB), K S Hegde Medical Academy (IN)
Openalex Percentile: Top 44%
Radiomics and Machine Learning in Medical Imaging
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