Machine learning in neuro-oncology: toward novel development fields.
Artificial intelligence
Brain tumors
Central nervous system malignancies
Deep learning
Machine learning
Journal
Journal of neuro-oncology
ISSN: 1573-7373
Titre abrégé: J Neurooncol
Pays: United States
ID NLM: 8309335
Informations de publication
Date de publication:
Sep 2022
Sep 2022
Historique:
received:
17
03
2022
accepted:
11
06
2022
pubmed:
28
6
2022
medline:
31
8
2022
entrez:
27
6
2022
Statut:
ppublish
Résumé
Artificial Intelligence (AI) involves several and different techniques able to elaborate a large amount of data responding to a specific planned outcome. There are several possible applications of this technology in neuro-oncology. We reviewed, according to PRISMA guidelines, available studies adopting AI in different fields of neuro-oncology including neuro-radiology, pathology, surgery, radiation therapy, and systemic treatments. Neuro-radiology presented the major number of studies assessing AI. However, this technology is being successfully tested also in other operative settings including surgery and radiation therapy. In this context, AI shows to significantly reduce resources and costs maintaining an elevated qualitative standard. Pathological diagnosis and development of novel systemic treatments are other two fields in which AI showed promising preliminary data. It is likely that AI will be quickly included in some aspects of daily clinical practice. Possible applications of these techniques are impressive and cover all aspects of neuro-oncology.
Identifiants
pubmed: 35761160
doi: 10.1007/s11060-022-04068-7
pii: 10.1007/s11060-022-04068-7
doi:
Types de publication
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
333-346Informations de copyright
© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
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