O
Omar Arnaout
Researcher at Brigham and Women's Hospital
Publications - 73
Citations - 2706
Omar Arnaout is an academic researcher from Brigham and Women's Hospital. The author has contributed to research in topics: Medicine & Internal medicine. The author has an hindex of 18, co-authored 51 publications receiving 1643 citations. Previous affiliations of Omar Arnaout include Harvard University & Northwestern University.
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Journal ArticleDOI
Artificial intelligence in cancer imaging: Clinical challenges and applications.
Wenya Linda Bi,Ahmed Hosny,Matthew B. Schabath,Maryellen L. Giger,Nicolai Juul Birkbak,Nicolai Juul Birkbak,Alireza Mehrtash,Alireza Mehrtash,Tavis Allison,Tavis Allison,Omar Arnaout,Christopher Abbosh,Christopher Abbosh,Ian F. Dunn,Raymond H. Mak,Rulla M. Tamimi,Clare M. Tempany,Charles Swanton,Charles Swanton,Udo Hoffmann,Lawrence H. Schwartz,Lawrence H. Schwartz,Robert J. Gillies,Raymond Y. Huang,Hugo J.W.L. Aerts,Hugo J.W.L. Aerts +25 more
TL;DR: The authors review the current state of AI as applied to medical imaging of cancer and describe advances in 4 tumor types to illustrate how common clinical problems are being addressed.
Journal ArticleDOI
Residual Convolutional Neural Network for the Determination of IDH Status in Low- and High-Grade Gliomas from MR Imaging
Ken Chang,Harrison X. Bai,Hao Zhou,Chang Su,Wenya Linda Bi,Ena Agbodza,Vasileios K. Kavouridis,Joeky T. Senders,Alessandro Boaro,Andrew Beers,Biqi Zhang,Alexandra Capellini,Weihua Liao,Qin Shen,Xuejun Li,Bo Xiao,Jane Cryan,Shakti Ramkissoon,Lori A. Ramkissoon,Keith L. Ligon,Patrick Y. Wen,Ranjit S. Bindra,John H. Woo,Omar Arnaout,Elizabeth R. Gerstner,Paul J. Zhang,Bruce R. Rosen,Li Yang,Raymond Y. Huang,Jayashree Kalpathy-Cramer +29 more
TL;DR: A deep learning technique is developed to noninvasively predict IDH genotype in grade II–IV glioma using conventional MR imaging using a multi-institutional data set.
Journal ArticleDOI
Machine Learning and Neurosurgical Outcome Prediction: A Systematic Review
Joeky T. Senders,Patrick Staples,Aditya V. Karhade,Mark M. Zaki,William B. Gormley,Marike L. D. Broekman,Timothy R. Smith,Omar Arnaout +7 more
TL;DR: Based on the specific prediction task evaluated and the type of input features included, ML models predicted outcomes after neurosurgery with a median accuracy and area under the receiver operating curve of 94.5% and 0.83, respectively.
Journal ArticleDOI
Natural and Artificial Intelligence in Neurosurgery: A Systematic Review.
Joeky T. Senders,Joeky T. Senders,Omar Arnaout,Omar Arnaout,Aditya V. Karhade,Hormuzdiyar H. Dasenbrock,William B. Gormley,Marike L. D. Broekman,Marike L. D. Broekman,Timothy R. Smith +9 more
TL;DR: It is concluded that ML models have the potential to augment the decision‐making capacity of clinicians in neurosurgical applications; however, significant hurdles remain associated with creating, validating, and deploying ML models in the clinical setting.
Journal ArticleDOI
Posterior fossa arteriovenous malformations.
Omar Arnaout,Bradley A. Gross,Christopher S. Eddleman,Bernard R. Bendok,Christopher C. Getch,H. Hunt Batjer +5 more
TL;DR: The authors reviewed the literature on posterior fossa AVMs, finding their annual rupture rates to be as high as 11.6%, an important factor that underscores the importance of aggressive treatment of lesions amenable to intervention as therapeutic options and results continue to improve.