TY  - JOUR
A1  - Sotoudeh, Houman
A1  - Shafaat, Omid
A1  - Bernstock, Joshua D.
A1  - Brooks, David
A1  - Elsayed, Galal
A1  - Chen, Jason A.
A1  - Szerip, Paul
A1  - Chagoya, Gustavo
A1  - Geßler, Florian
A1  - Sotoudeh, Ehsan
A1  - Shafaat, Amir
A1  - Friedman, Gregory K.
T1  - Artificial intelligence in the management of glioma: Era of personalized medicine
T2  - Frontiers in oncology
N2  - Purpose: Artificial intelligence (AI) has accelerated novel discoveries across multiple disciplines including medicine. Clinical medicine suffers from a lack of AI-based applications, potentially due to lack of awareness of AI methodology. Future collaboration between computer scientists and clinicians is critical to maximize the benefits of transformative technology in this field for patients. To illustrate, we describe AI-based advances in the diagnosis and management of gliomas, the most common primary central nervous system (CNS) malignancy.
Methods: Presented is a succinct description of foundational concepts of AI approaches and their relevance to clinical medicine, geared toward clinicians without computer science backgrounds. We also review novel AI approaches in the diagnosis and management of glioma.
Results: Novel AI approaches in gliomas have been developed to predict the grading and genomics from imaging, automate the diagnosis from histopathology, and provide insight into prognosis.
Conclusion: Novel AI approaches offer acceptable performance in gliomas. Further investigation is necessary to improve the methodology and determine the full clinical utility of these novel approaches.
KW  - glioma
KW  - artificial intelligence
KW  - neural network
KW  - deep neural network
KW  - convolution neural network
KW  - support vector machines
Y1  - 2019
UR  - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/51867
UR  - https://nbn-resolving.org/urn:nbn:de:hebis:30:3-518678
SN  - 2234-943X
N1  - Copyright © 2019 Sotoudeh, Shafaat, Bernstock, Brooks, Elsayed, Chen, Szerip, Chagoya, Gessler, Sotoudeh, Shafaat and Friedman. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
VL  - 9
IS  - Art. 768
SP  - 1
EP  - 11
PB  - Frontiers Media
CY  - Lausanne
ER  -