Artificial intelligence in breast surgery - Current applications, challenges, and future perspectives

Sep 23, 2026

Artificial intelligence in breast cancer surgery enhances precision, accuracy, and personalized treatment strategies across the full surgical continuum. This narrative review synthesizes AI applications from preoperative planning through intraoperative decision support and postoperative management. A structured search of PubMed, Scopus, and Web of Science over 15 years identified studies covering tumor detection, segmentation, surgical margin assessment, real-time imaging guidance, robotics, and predictive analytics for complications and recurrence monitoring, while addressing translational gaps and clinical readiness concerns.

LanguageEnglish

CategoryHealthcare

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Pages16

Reading Time40 min

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Artificial intelligence in breast surgery: Current applications, challenges, and future perspectives Mahtab Khajeh 1, Pezhman Farshidmehr2, Ehsan Rahimpour3, Parastoo Amiri4 and Mohammad Amin Shahram 1,5 Journal of International Medical Research 2026, Vol. 54(1) 1–16! The Author(s) 2026 Article reuse guidelines: [sagepub.com/journals-permissions](sagepub.com/journals-permissions)[ ](sagepub.com/journals-permissions)[DOI: 10.1177/03000605251412124](DOI: 10.1177/03000605251412124)[ ](DOI: 10.1177/03000605251412124)[journals.sagepub.com/home/imr](journals.sagepub.com/home/imr) Abstract The use of artificial intelligence is changing the landscape of breast cancer surgery through enhanced precision, accuracy, and personalized treatment strategies. This narrative review assessed artificial intelligence applications across the surgical stages of care in breast cancer surgery, including preoperative planning, intraoperative assistance, and postoperative care. A structured literature search of PubMed, Scopus, and Web of Science over the past 15 years was conducted to identify studies on artificial intelligence applications across all stages of breast cancer surgery. In the preoperative phase, artificial intelligence contributes to tumor detection, segmentation, and surgical margin assessment through advanced imaging and predictive modeling. During surgery, real-time image-guided systems and robotic platforms powered by machine learning enable greater accuracy and intraoperative decision support. Postoperatively, artificial intelligence–driven tools aid in complication prediction, recurrence monitoring, and follow-up personalization, thereby improving patient outcomes and reducing variability in care. Integration of multimodal artificial intelligence approaches from imaging, robotics, and predictive analytics across the surgical continuum can help highlight translational gaps and evaluate clinical readiness, providing insights that have not been emphasized in previous reviews. Despite these advancements, many artificial intelligence applications remain in early research stages or have limited clinical use, facing challenges in data standardization, model interpretability, ethics, and integration into practice. Clinical impact depends on infrastructure, surgeon expertise, and regulations. 1 Non-Communicable Diseases Research Center, Sabzevar University of Medical Sciences, Iran 2Department of Vascular Surgery, School of Medicine, Sina Hospital, Tehran University of Medical Sciences, Iran 3Department of Surgery, School of Medicine, Sina Hospital, Tehran University of Medical Sciences, Iran 4Clinical Research Development Unit, Vasei Hospital, Sabzevar University of Medical Sciences, Iran 5Department of Medical Physics and Radiological Sciences, Sabzevar University of Medical Sciences, Iran Corresponding author: Mohammad Amin Shahram, Sabzevar University of Medical Sciences, Sabzevar, 96135, Iran. Email: [aminshahram530@gmail.com](aminshahram530@gmail.com) Creative Commons Non Commercial CC BY-NC: This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License ([https://creativecommons.org/licenses/by-nc/4.0/](https://creativecommons.org/licenses/by-nc/4.0/)) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages ([https://us.sagepub.com/en-us/nam/open-access-at-sage](https://us.sagepub.com/en-us/nam/open-access-at-sage)). Nevertheless, interdisciplinary collaboration allows artificial intelligence to enhance accuracy, reduce complications, and improve patient-centered care in breast cancer surgery. Keywords Artificial intelligence, breast surgery, machine learning, personalized medicine, surgical care Date received: 20 August 2025; accepted: 15 December 2025 Introduction Recent advances in artificial intelligence (AI) are reshap

FAQs

How does artificial intelligence support preoperative planning in breast cancer surgery?

AI contributes to tumor detection, segmentation, and surgical margin assessment using advanced imaging and predictive modeling.

What role can AI play during surgery?

Real-time image-guided systems and robotic platforms, powered by machine learning, can improve accuracy and provide intraoperative decision support.

What major challenges limit clinical adoption of AI in breast surgery?

Key barriers include data standardization, model interpretability, ethical considerations, and integration into clinical practice, with impact depending on infrastructure, surgeon expertise, and regulations.

Sep 23, 2026

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