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Recent Outcomes and Challenges of Artificial Intelligence, Machine Learning, and Deep Learning in Neurosurgery

Authors :
Wireko Andrew Awuah
Favour Tope Adebusoye
Jack Wellington
Lian David
Abdus Salam
Amanda Leong Weng Yee
Edouard Lansiaux
Rohan Yarlagadda
Tulika Garg
Toufik Abdul-Rahman
Jacob Kalmanovich
Goshen David Miteu
Mrinmoy Kundu
Nikitina Iryna Mykolaivna
Source :
World Neurosurgery: X, Vol 23, Iss , Pp 100301- (2024)
Publication Year :
2024
Publisher :
Elsevier, 2024.

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.

Details

Language :
English
ISSN :
25901397
Volume :
23
Issue :
100301-
Database :
Directory of Open Access Journals
Journal :
World Neurosurgery: X
Publication Type :
Academic Journal
Accession number :
edsdoj.4444eded15f94c82aa9ba7c99399d63f
Document Type :
article
Full Text :
https://doi.org/10.1016/j.wnsx.2024.100301