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Neurosurgical Management of Cerebrospinal Tumors in the Era of Artificial Intelligence : A Scoping Review

Central nervous system tumors are identified as tumors of the brain and spinal cord. The associated morbidity and mortality of cerebrospinal tumors are disproportionately high compared to other malignancies. While minimally invasive techniques have initiated a revolution in neurosurgery, artificial...

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Autores principales: Agadi, Kuchalambal, Dominari, Asimina, Tebha, Sameer Saleem, Mohammadi, Asma, Zahid, Samina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korean Neurosurgical Society 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10641423/
https://www.ncbi.nlm.nih.gov/pubmed/35831137
http://dx.doi.org/10.3340/jkns.2021.0213
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author Agadi, Kuchalambal
Dominari, Asimina
Tebha, Sameer Saleem
Mohammadi, Asma
Zahid, Samina
author_facet Agadi, Kuchalambal
Dominari, Asimina
Tebha, Sameer Saleem
Mohammadi, Asma
Zahid, Samina
author_sort Agadi, Kuchalambal
collection PubMed
description Central nervous system tumors are identified as tumors of the brain and spinal cord. The associated morbidity and mortality of cerebrospinal tumors are disproportionately high compared to other malignancies. While minimally invasive techniques have initiated a revolution in neurosurgery, artificial intelligence (AI) is expediting it. Our study aims to analyze AI’s role in the neurosurgical management of cerebrospinal tumors. We conducted a scoping review using the Arksey and O’Malley framework. Upon screening, data extraction and analysis were focused on exploring all potential implications of AI, classification of these implications in the management of cerebrospinal tumors. AI has enhanced the precision of diagnosis of these tumors, enables surgeons to excise the tumor margins completely, thereby reducing the risk of recurrence, and helps to make a more accurate prediction of the patient’s prognosis than the conventional methods. AI also offers real-time training to neurosurgeons using virtual and 3D simulation, thereby increasing their confidence and skills during procedures. In addition, robotics is integrated into neurosurgery and identified to increase patient outcomes by making surgery less invasive. AI, including machine learning, is rigorously considered for its applications in the neurosurgical management of cerebrospinal tumors. This field requires further research focused on areas clinically essential in improving the outcome that is also economically feasible for clinical use. The authors suggest that data analysts and neurosurgeons collaborate to explore the full potential of AI.
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spelling pubmed-106414232023-11-15 Neurosurgical Management of Cerebrospinal Tumors in the Era of Artificial Intelligence : A Scoping Review Agadi, Kuchalambal Dominari, Asimina Tebha, Sameer Saleem Mohammadi, Asma Zahid, Samina J Korean Neurosurg Soc Review Article Central nervous system tumors are identified as tumors of the brain and spinal cord. The associated morbidity and mortality of cerebrospinal tumors are disproportionately high compared to other malignancies. While minimally invasive techniques have initiated a revolution in neurosurgery, artificial intelligence (AI) is expediting it. Our study aims to analyze AI’s role in the neurosurgical management of cerebrospinal tumors. We conducted a scoping review using the Arksey and O’Malley framework. Upon screening, data extraction and analysis were focused on exploring all potential implications of AI, classification of these implications in the management of cerebrospinal tumors. AI has enhanced the precision of diagnosis of these tumors, enables surgeons to excise the tumor margins completely, thereby reducing the risk of recurrence, and helps to make a more accurate prediction of the patient’s prognosis than the conventional methods. AI also offers real-time training to neurosurgeons using virtual and 3D simulation, thereby increasing their confidence and skills during procedures. In addition, robotics is integrated into neurosurgery and identified to increase patient outcomes by making surgery less invasive. AI, including machine learning, is rigorously considered for its applications in the neurosurgical management of cerebrospinal tumors. This field requires further research focused on areas clinically essential in improving the outcome that is also economically feasible for clinical use. The authors suggest that data analysts and neurosurgeons collaborate to explore the full potential of AI. Korean Neurosurgical Society 2023-11 2022-07-14 /pmc/articles/PMC10641423/ /pubmed/35831137 http://dx.doi.org/10.3340/jkns.2021.0213 Text en Copyright © 2023 The Korean Neurosurgical Society https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0 (https://creativecommons.org/licenses/by-nc/4.0/) ) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Review Article
Agadi, Kuchalambal
Dominari, Asimina
Tebha, Sameer Saleem
Mohammadi, Asma
Zahid, Samina
Neurosurgical Management of Cerebrospinal Tumors in the Era of Artificial Intelligence : A Scoping Review
title Neurosurgical Management of Cerebrospinal Tumors in the Era of Artificial Intelligence : A Scoping Review
title_full Neurosurgical Management of Cerebrospinal Tumors in the Era of Artificial Intelligence : A Scoping Review
title_fullStr Neurosurgical Management of Cerebrospinal Tumors in the Era of Artificial Intelligence : A Scoping Review
title_full_unstemmed Neurosurgical Management of Cerebrospinal Tumors in the Era of Artificial Intelligence : A Scoping Review
title_short Neurosurgical Management of Cerebrospinal Tumors in the Era of Artificial Intelligence : A Scoping Review
title_sort neurosurgical management of cerebrospinal tumors in the era of artificial intelligence : a scoping review
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10641423/
https://www.ncbi.nlm.nih.gov/pubmed/35831137
http://dx.doi.org/10.3340/jkns.2021.0213
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