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Artificial Intelligence for Response Assessment in Neuro Oncology (AI-RANO), part 1: review of current advancements.

Authors :
Villanueva-Meyer, Javier E
Bakas, Spyridon
Tiwari, Pallavi
Lupo, Janine M
Calabrese, Evan
Davatzikos, Christos
Bi, Wenya Linda
Ismail, Marwa
Akbari, Hamed
Lohmann, Philipp
Booth, Thomas C
Wiestler, Benedikt
Aerts, Hugo J W L
Rasool, Ghulam
Tonn, Joerg C
Nowosielski, Martha
Jain, Rajan
Colen, Rivka R
Pati, Sarthak
Baid, Ujjwal
Source :
Lancet Oncology. Nov2024, Vol. 25 Issue 11, pe581-e588. 8p.
Publication Year :
2024

Abstract

The development, application, and benchmarking of artificial intelligence (AI) tools to improve diagnosis, prognostication, and therapy in neuro-oncology are increasing at a rapid pace. This Policy Review provides an overview and critical assessment of the work to date in this field, focusing on diagnostic AI models of key genomic markers, predictive AI models of response before and after therapy, and differentiation of true disease progression from treatment-related changes, which is a considerable challenge based on current clinical care in neuro-oncology. Furthermore, promising future directions, including the use of AI for automated response assessment in neuro-oncology, are discussed. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
14702045
Volume :
25
Issue :
11
Database :
Academic Search Index
Journal :
Lancet Oncology
Publication Type :
Academic Journal
Accession number :
180494855
Full Text :
https://doi.org/10.1016/S1470-2045(24)00316-4