Recent outcomes and challenges of artificial intelligence, machine learning and deep learning applications in neurosurgery

Awuah, Wireko Andrew, Adebusoye, Favour Tope, Wellington, Jack, David, Lian, Salam, Abdus, Weng Yee, Amanda Leong, Lansiaux, Edouard, Yarlagadda, Rohan, Garg, Tulika, Abdul-Rahman, Toufik, Kalmanovich, Jacob, Miteu, Goshen David, Kundu, Mrinmoy and Mykolaivna, Nikitina Iryna 2024. Recent outcomes and challenges of artificial intelligence, machine learning and deep learning applications in neurosurgery. World Neurosurgery: X 23 , 100301. 10.1016/j.wnsx.2024.100301

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Abstract

Neurosurgeons receive extensive technical training, which equips them with the knowledge and skills to specialise in various fields and manage the massive amounts of information and decision-making required throughout the various stages of neurosurgery, including preoperative, intraoperative, and postoperative care and recovery. Over the past few years, artificial intelligence (AI) has become more useful in neurosurgery. AI has the potential to improve patient outcomes by augmenting the capabilities of neurosurgeons and ultimately improving diagnostic and prognostic outcomes as well as decision-making during surgical procedures. By incorporating AI into both interventional and non-interventional therapies, neurosurgeons may provide the best care for their patients. AI, machine learning (ML), and deep learning (DL) have made significant progress in the field of neurosurgery. These cutting-edge methods have enhanced patient outcomes, reduced complications, and improved surgical planning.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Medicine
Additional Information:	License information from Publisher: LICENSE 1: URL: http://creativecommons.org/licenses/by-nc-nd/4.0/, Start Date: 2024-02-21
Publisher:	Elsevier
ISSN:	2590-1397
Date of First Compliant Deposit:	11 March 2024
Date of Acceptance:	21 February 2024
Last Modified:	08 Apr 2024 13:12
URI:	https://orca.cardiff.ac.uk/id/eprint/167100

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