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The Role of Artificial Intelligence and Machine Learning in Surgery

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Robotic Urologic Surgery

Abstract

The intersection of artificial intelligence (AI) and medicine has resulted in remarkable accomplishments in the past few years. Surgery is no exception to this trend. Taking advantage of the abundant data from electronic medical records and the operating room, a variety of AI models (e.g., machine learning, computer vision, and natural language processing) have served as powerful tools to facilitate every aspect of surgery—from preoperative patient selection to postoperative outcome prediction; from intraoperative intelligent assistance to semiautonomous surgery; and from objective surgical assessment to real-time surgical feedback. The application of AI is still rapidly expanding. However, certain issues brought by AI still concern people, including data privacy, cyber security, model transparency, study reproducibility, bias and inequality, and accountability and liability. By reviewing recent studies in this field and discussing relevant ethical and legal issues, this chapter offers an overview of the current application of AI in the surgical field, and provides some insights about how to avoid the backlash of this involving technology.

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Author information

Authors and Affiliations

  1. Catherine and Joseph Aresty Department of Urology, Center for Robotic Simulation and Education, USC Institute of Urology, University of Southern California, Los Angeles, CA, USA

    Runzhuo Ma & Andrew J. Hung

  2. Division of Surgery and Interventional Science, Research Department of Targeted Intervention, University College London, London, UK

    Justin W. Collins

  3. Wellcome/ESPRC Centre for Interventional and Surgical Sciences (WEISS), University College London, London, UK

    Justin W. Collins

  4. Division of Uro-oncology, University College London Hospital, London, UK

    Justin W. Collins

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  2. Justin W. Collins
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  3. Andrew J. Hung
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Editors and Affiliations

  1. Department of Urology, Icahn School of Medicine at Mount Sinai, New York, USA

    Peter Wiklund

  2. Department of Urology, ORSI Academy, Aalst, Belgium

    Alexandre Mottrie

  3. Pediatric Urology, University of Chicago Medicine and Biological Sciences, Chicago, IL, USA

    Mohan S Gundeti

  4. Urology, Global Robotics Institute, Celebration, FL, USA

    Vipul Patel

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Ma, R., Collins, J.W., Hung, A.J. (2022). The Role of Artificial Intelligence and Machine Learning in Surgery. In: Wiklund, P., Mottrie, A., Gundeti, M.S., Patel, V. (eds) Robotic Urologic Surgery. Springer, Cham. https://doi.org/10.1007/978-3-031-00363-9_9

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  • DOI: https://doi.org/10.1007/978-3-031-00363-9_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-00362-2

  • Online ISBN: 978-3-031-00363-9

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