The Clinical Application of Artificial Intelligence in Breast Imaging: Current Insights, Challenges, and Future Directions

Artificial intelligence (AI) is used in various areas of radiology, particularly in breast imaging, starting with mammography and extending to ultrasonography (US) and magnetic resonance imaging (MRI). This overview aims to examine the introduction, applications, and challenges of AI in breast imaging. This narrative outlines the applications of AI in various modalities-including mammography, US, and MRI-and discusses its indications, ongoing challenges, and future perspectives. AI has been used for identification, classification, detection, diagnosis, breast density assessment, treatment response, and prediction of prognosis. AI can help radiologists avoid missed diagnoses due to heavy workloads and enhance workflow efficiency. The integration of AI software into daily practice, along with further validation and refinement, is necessary to support radiologists' workflows.

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Publication Details

Journal
Journal of Breast Cancer
Published
2025-01-01
DOI
https://doi.org/10.4048/jbc.2025.0123
Citations
1
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
1.36
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article

The Clinical Application of Artificial Intelligence in Breast Imaging: Current Insights, Challenges, and Future Directions

Eun Jee Song, Yu‐Mee Sohn
1 citations
Journal of Breast Cancer
Radiomics and Machine Learning in Medical Imaging
1.36
article

The Clinical Application of Artificial Intelligence in Breast Imaging: Current Insights, Challenges, and Future Directions

Eun Jee Song, Yu‐Mee Sohn
article en
1 citations

Abstract

Artificial intelligence (AI) is used in various areas of radiology, particularly in breast imaging, starting with mammography and extending to ultrasonography (US) and magnetic resonance imaging (MRI). This overview aims to examine the introduction, applications, and challenges of AI in breast imaging. This narrative outlines the applications of AI in various modalities-including mammography, US, and MRI-and discusses its indications, ongoing challenges, and future perspectives. AI has been used for identification, classification, detection, diagnosis, breast density assessment, treatment response, and prediction of prognosis. AI can help radiologists avoid missed diagnoses due to heavy workloads and enhance workflow efficiency. The integration of AI software into daily practice, along with further validation and refinement, is necessary to support radiologists' workflows.

Journal of Breast CancerVol. 28(5)
Kyung Hee University (KR), Hallym University Kangnam Sacred Heart Hospital (KR), Sacred Heart Hospital (US)
Openalex Percentile: Top 16%
Radiomics and Machine Learning in Medical Imaging
1.36
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