Novel applications of deep learning in surgical training
Author | Shidin, Balakrishnan |
Author | Dakua, Sarada Prasad |
Author | El Ansari, Walid |
Author | Aboumarzouk, Omar |
Author | Al Ansari, Abdulla |
Available date | 2024-10-28T10:44:15Z |
Publication Date | 2023 |
Publication Name | Artificial Intelligence, Big Data, Blockchain and 5G for the Digital Transformation of the Healthcare Industry: a Movement Toward more Resilient and Inclusive Societies |
Resource | Scopus |
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. |
Language | en |
Publisher | Elsevier |
Subject | Artificial intelligence Deep learning Surgery Surgical training |
Type | Book chapter |
Pagination | 301-320 |
Check access options
Files in this item
Files | Size | Format | View |
---|---|---|---|
There are no files associated with this item. |
This item appears in the following Collection(s)
-
Medicine Research [1483 items ]