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    Novel applications of deep learning in surgical training

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    Date
    2023
    Author
    Shidin, Balakrishnan
    Dakua, Sarada Prasad
    El Ansari, Walid
    Aboumarzouk, Omar
    Al Ansari, Abdulla
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    Abstract
    This chapter explores the novel applications of artificial intelligence (AI), specifically deep learning (DL) in surgical training. It aims to clarify the concepts associated with DL and address implementation approaches that integrate DL techniques with simulation and virtual reality, intelligent tutoring systems, augmented reality, robotic-assisted surgery, and data-driven personalized training. The chapter examines the innovative role of DL in creating realistic surgical simulations, enhancing adaptive learning experiences, and facilitating real-time feedback. The potential of DL to revolutionize surgical training, improve skill acquisition speed, and elevate patient outcomes is emphasized. Challenges, such as data availability, model transparency, and ethical considerations, are discussed. The chapter underscores the importance of interdisciplinary collaboration between surgeons, educators, and AI experts for the successful integration and future development of DL in surgical training.
    DOI/handle
    http://dx.doi.org/10.1016/B978-0-443-21598-8.00021-X
    http://hdl.handle.net/10576/60652
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    • Medicine Research [‎1819‎ items ]

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