Artificial Intelligence in Neuro-Oncology: predicting molecular markers and response to therapy.

Main Article Content

Mana Moassefi Shahriar Faghani Bradley J. Erickson

Abstract

Artificial intelligence’s capability to analyze and interpret complex data is transforming neuro-oncology by enhancing the precision of diagnosis and enabling personalized treatment plans. Particularly, applications in radiogenomics are instrumental in identifying molecular markers from imaging data, potentially reducing the need for invasive procedures and accelerating molecular diagnostics. This review discusses various artificial intelligence methodologies, from machine learning to deep learning, mentioning a number of their current use cases and the challenges faced in clinical integration. In addition, future directions, such as multimodal data integration and the need to address technical and ethical implications, are highlighted.

Keywords: Radiogenomic, Neuro-oncology, Artificial Intelligence, Treatment

Article Details

How to Cite
MOASSEFI, Mana; FAGHANI, Shahriar; ERICKSON, Bradley J.. Artificial Intelligence in Neuro-Oncology: predicting molecular markers and response to therapy.. Medical Research Archives, [S.l.], v. 12, n. 6, june 2024. ISSN 2375-1924. Available at: <https://esmed.org/MRA/mra/article/view/5523>. Date accessed: 22 july 2024. doi: https://doi.org/10.18103/mra.v12i6.5523.
Section
Review Articles

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