Present and future of machine learning in breast surgery: systematic review

Abstract

Background Machine learning is a set of models and methods that can automatically detect patterns in vast amounts of data, extract information, and use it to perform decision-making under uncertain conditions. The potential of machine learning is significant, and breast surgeons must strive to be informed with up-to-date knowledge and its applications. Methods A systematic database search of Embase, MEDLINE, the Cochrane database, and Google Scholar, from inception to December 2021, was conducted of original articles that explored the use of machine learning and/or artificial intelligence in breast surgery in EMBASE, MEDLINE, Cochrane database and Google Scholar. Results The search yielded 477 articles, of which 14 studies were included in this review, featuring 73 847 patients. Four main areas of machine learning application were identified: predictive modelling of surgical outcomes; breast imaging-based context; screening and triaging of patients with breast cancer; and as network utility for detection. There is evident value of machine learning in preoperative planning and in providing information for surgery both in a cancer and an aesthetic context. Machine learning outperformed traditional statistical modelling in all studies for predicting mortality, morbidity, and quality of life outcomes. Machine learning patterns and associations could support planning, anatomical visualization, and surgical navigation. Conclusion Machine learning demonstrated promising applications for improving breast surgery outcomes and patient-centred care. Neveretheless, there remain important limitations and ethical concerns relating to implementing artificial intelligence into everyday surgical practices.

Innovations and Challenges in Breast Cancer Care: A Review

“…AI-powered tools, such as computer-aided detection (CAD) systems, are increasingly used in clinical practice to assist radiologists in breast cancer screening and diagnosis. Virtual reality (VR) and augmented reality (AR) technologies are also being utilized to enhance surgical visualization and training [ 3 , 4 ].…”

“…While there have been significant advancements in breast cancer care, several challenges have arisen along with these innovations. Some of the difficulties associated with these advancements include [ 2 , 3 , 4 ]:…”

“…Circumstances created by the COVID-19 pandemic have led to increased telemedicine use and have modified follow-up protocols and radiotherapy delivery methods. Additionally, with the use of more advanced prognostic and predictive tests, unnecessary/over-diagnosis, treatments, and hospital admissions [ 2 , 3 , 4 ] can be avoided.…”

Evaluating the ability of an artificial-intelligence cloud-based platform designed to provide information prior to locoregional therapy for breast cancer in improving patient’s satisfaction with therapy: The CINDERELLA trial

“…The potential applications of AI in breast surgery vary from screening and diagnosis to prediction models and decision support systems. Current literature provides sufficient groundwork to build up randomized prospective trials studying the impact of AI in clinical practice [ 21 ]. Table 3 summarizes the ultimate clinical need for the CINDERELLA APProach.…”

Use of Artificial Intelligence in the Advancement of Breast Surgery and Implications for Breast Reconstruction: A Narrative Review

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