@article{a97ce9a3dbd640b4b0ca4112aad50e27,
title = "Data-efficient deep learning of radiological image data for outcome prediction after endovascular treatment of patients with acute ischemic stroke",
keywords = "Acute ischemic stroke, Radiological images, Deep learning, Prognostics, ResNet, RFNN, Structured receptive fields, Gradient-weighted class activation mapping, COMPUTED-TOMOGRAPHY, ANGIOGRAPHY, SCORE",
author = "A. Hilbert and Ramos, {L. A.} and {van Os}, {H. J. A.} and Olabarriaga, {S. D.} and Tolhuisen, {M. L.} and Wermer, {M. J. H.} and Barros, {R. S.} and {van der Schaaf}, I. and D. Dippel and Roos, {Y. B. W. E. M.} and {van Zwam}, {W. H.} and Yoo, {A. J.} and Emmer, {B. J.} and Nijeholt, {G. J. Lycklama a} and Zwinderman, {A. H.} and Strijkers, {G. J.} and Majoie, {C. B. L. M.} and Marquering, {H. A.}",
year = "2019",
month = dec,
doi = "10.1016/j.compbiomed.2019.103516",
language = "English",
volume = "115",
journal = "Computers in Biology and Medicine",
issn = "0010-4825",
publisher = "Elsevier Science",
}