Journal
Frontiers in Neuroinformatics
Publication Date
2019
Volume
13
First Page
53
Document Type
Open Access Publication
DOI
10.3389/fninf.2019.00053
Rights and Permissions
Chauhan S, Vig L, De Filippo De Grazia M, Corbetta M, Ahmad S and Zorzi M (2019) A Comparison of Shallow and Deep Learning Methods for Predicting Cognitive Performance of Stroke Patients From MRI Lesion Images. Front. Neuroinform. 13:53. doi: 10.3389/fninf.2019.00053 © 2019 Chauhan, Vig, De Filippo De Grazia, Corbetta, Ahmad and Zorzi. 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.
Recommended Citation
Chauhan, Sucheta; Vig, Lovekesh; De Filippo De Grazia, Michele; Corbetta, Maurizio; Ahmad, Shandar; and Zorzi, Marco, "A comparison of shallow and deep learning methods for predicting cognitive performance of stroke patients from MRI lesion images." Frontiers in Neuroinformatics. 13, 53 (2019).
https://digitalcommons.wustl.edu/open_access_pubs/8064
