James M. Brown
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Citado por
Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge
S Bakas, M Reyes, A Jakab, S Bauer, M Rempfler, A Crimi, RT Shinohara, ...
arXiv preprint arXiv:1811.02629, 2018
High-throughput discovery of novel developmental phenotypes
ME Dickinson, AM Flenniken, X Ji, L Teboul, MD Wong, JK White, ...
Nature 537 (7621), 508-514, 2016
Automated diagnosis of plus disease in retinopathy of prematurity using deep convolutional neural networks
JM Brown, JP Campbell, A Beers, K Chang, S Ostmo, RVP Chan, J Dy, ...
JAMA ophthalmology 136 (7), 803-810, 2018
Distributed deep learning networks among institutions for medical imaging
K Chang, N Balachandar, C Lam, D Yi, J Brown, A Beers, B Rosen, ...
Journal of the American Medical Informatics Association 25 (8), 945-954, 2018
Disease model discovery from 3,328 gene knockouts by The International Mouse Phenotyping Consortium
TF Meehan, N Conte, DB West, JO Jacobsen, J Mason, J Warren, ...
Nature genetics 49 (8), 1231-1238, 2017
Automatic assessment of glioma burden: a deep learning algorithm for fully automated volumetric and bidimensional measurement
K Chang, AL Beers, HX Bai, JM Brown, KI Ly, X Li, JT Senders, ...
Neuro-oncology 21 (11), 1412-1422, 2019
ISLES 2016 and 2017-benchmarking ischemic stroke lesion outcome prediction based on multispectral MRI
S Winzeck, A Hakim, R McKinley, JA Pinto, V Alves, C Silva, M Pisov, ...
Frontiers in neurology, 679, 2018
Evaluation of a deep learning image assessment system for detecting severe retinopathy of prematurity
TK Redd, JP Campbell, JM Brown, SJ Kim, S Ostmo, RVP Chan, J Dy, ...
British Journal of Ophthalmology 103 (5), 580-584, 2019
High-resolution medical image synthesis using progressively grown generative adversarial networks
A Beers, J Brown, K Chang, JP Campbell, S Ostmo, MF Chiang, ...
arXiv preprint arXiv:1805.03144, 2018
Monitoring disease progression with a quantitative severity scale for retinopathy of prematurity using deep learning
S Taylor, JM Brown, K Gupta, JP Campbell, S Ostmo, RVP Chan, J Dy, ...
JAMA ophthalmology 137 (9), 1022-1028, 2019
Siamese neural networks for continuous disease severity evaluation and change detection in medical imaging
MD Li, K Chang, B Bearce, CY Chang, AJ Huang, JP Campbell, ...
NPJ digital medicine 3 (1), 48, 2020
Applications of artificial intelligence for retinopathy of prematurity screening
JP Campbell, P Singh, TK Redd, JM Brown, PK Shah, P Subramanian, ...
Pediatrics 147 (3), 2021
A quantitative severity scale for retinopathy of prematurity using deep learning to monitor disease regression after treatment
K Gupta, JP Campbell, S Taylor, JM Brown, S Ostmo, RVP Chan, J Dy, ...
JAMA ophthalmology 137 (9), 1029-1036, 2019
Sequential 3D U-Nets for Biologically-Informed Brain Tumor Segmentation
A Beers, K Chang, J Brown, E Sartor, CP Mammen, E Gerstner, B Rosen, ...
arXiv preprint arXiv:1709.02967, 2017
Automated fundus image quality assessment in retinopathy of prematurity using deep convolutional neural networks
AS Coyner, R Swan, JP Campbell, S Ostmo, JM Brown, ...
Ophthalmology Retina 3 (5), 444-450, 2019
Evaluation of a Deep Learning–Derived Quantitative Retinopathy of Prematurity Severity Scale
JP Campbell, SJ Kim, JM Brown, S Ostmo, RVP Chan, J Kalpathy-Cramer, ...
Ophthalmology 128 (7), 1070-1076, 2021
DeepNeuro: an open-source deep learning toolbox for neuroimaging
A Beers, J Brown, K Chang, K Hoebel, J Patel, KI Ly, SM Tolaney, ...
Neuroinformatics, 1-14, 2020
Machine Learning Models can Detect Aneurysm Rupture and Identify Clinical Features Associated with Rupture
MA Silva, J Patel, V Kavouridis, T Gallerani, A Beers, K Chang, KV Hoebel, ...
World neurosurgery 131, e46-e51, 2019
Plus Disease in Retinopathy of Prematurity: Convolutional Neural Network Performance Using a Combined Neural Network and Feature Extraction Approach
VM Yildiz, P Tian, I Yildiz, JM Brown, J Kalpathy-Cramer, J Dy, S Ioannidis, ...
Translational Vision Science & Technology 9 (2), 10-10, 2020
Radiomics repeatability pitfalls in a scan-rescan MRI study of glioblastoma
KV Hoebel, JB Patel, AL Beers, K Chang, P Singh, JM Brown, MC Pinho, ...
Radiology: Artificial Intelligence 3 (1), e190199, 2020
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Artículos 1–20