|CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning|
NAY Rajpurkar P, Irvin J, Zhu K, Yang B, Mehta H, Duan T, Ding D, Bagul A ...
|Chexpert: A large chest radiograph dataset with uncertainty labels and expert comparison|
J Irvin, P Rajpurkar, M Ko, Y Yu, S Ciurea-Ilcus, C Chute, H Marklund, ...
Thirty-Third AAAI Conference on Artificial Intelligence, 2019
|Deep learning for chest radiograph diagnosis: A retrospective comparison of the CheXNeXt algorithm to practicing radiologists|
P Rajpurkar, J Irvin, RL Ball, K Zhu, B Yang, H Mehta, T Duan, D Ding, ...
PLoS medicine 15 (11), e1002686, 2018
|Deep-learning-assisted diagnosis for knee magnetic resonance imaging: Development and retrospective validation of MRNet|
N Bien, P Rajpurkar, RL Ball, J Irvin, A Park, E Jones, M Bereket, BN Patel, ...
PLoS medicine 15 (11), e1002699, 2018
|MURA Dataset: Towards Radiologist-Level Abnormality Detection in Musculoskeletal Radiographs|
NAY Rajpurkar P, Irvin J, Bagul A, Ding D, Duan T, Mehta H, Yang B, Zhu K ...
|Deep learning to classify radiology free-text reports|
MC Chen, RL Ball, L Yang, N Moradzadeh, BE Chapman, DB Larson, ...
Radiology 286 (3), 845-852, 2018
|Mura dataset: Towards radiologist-level abnormality detection in musculoskeletal radiographs|
P Rajpurkar, J Irvin, A Bagul, D Ding, T Duan, H Mehta, B Yang, K Zhu, ...
|Predicting the lethal phenotype of the knockout mouse by integrating comprehensive genomic data|
Y Yuan, Y Xu, J Xu, RL Ball, H Liang
Bioinformatics 28 (9), 1246-1252, 2012
|Deep Learning–Assisted Diagnosis of Cerebral Aneurysms Using the HeadXNet Model|
JAMA Network Open 2 (6), e195600-e195600, 2019
|Demonstration of artificial neural network in Matlab|
R Ball, P Tissot
Division of Nearhsore Research, Texas A&M University–Corpus Christi, 1-5, 2006
|Regulatory complexity revealed by integrated cytological and RNA-seq analyses of meiotic substages in mouse spermatocytes|
RL Ball, Y Fujiwara, F Sun, J Hu, MA Hibbs, MA Handel, GW Carter
BMC genomics 17 (1), 1-17, 2016
|Comparative analysis of somatic copy-number alterations across different human cancer types reveals two distinct classes of breakpoint hotspots|
Y Li, L Zhang, RL Ball, X Liang, J Li, Z Lin, H Liang
Human molecular genetics 21 (22), 4957-4965, 2012
|Evaluation of a Smartphone Decision-Support Tool for Diarrheal Disease Management in a Resource-Limited Setting|
F Haque, RL Ball, S Khatun, M Ahmed, S Kache, MJ Chisti, SA Sarker, ...
PLoS neglected tropical diseases 11 (1), e0005290, 2017
|Patient outcomes and cerebral infarction after ruptured anterior communicating artery aneurysm treatment|
JJ Heit, RL Ball, NA Telischak, HM Do, RL Dodd, GK Steinberg, ...
American Journal of Neuroradiology 38 (11), 2119-2125, 2017
|Comparison of random forest, artificial neural network, and multi-linear regression: a water temperature prediction case|
RL Ball, P Tissot, B Zimmer, B Sterba-Boatwright
Seventh conference on artificial intelligence and its applications to the …, 2009
|Neuroimaging radiological interpretation system for acute traumatic brain injury|
M Wintermark, Y Li, VY Ding, Y Xu, B Jiang, RL Ball, M Zeineh, A Gean, ...
Journal of neurotrauma 35 (22), 2665-2672, 2018
|Novel application of virtual reality in patient engagement for deep brain stimulation: A pilot study|
MK Collins, VY Ding, RL Ball, DL Dolce, JM Henderson, CH Halpern
Brain Stimulation: Basic, Translational, and Clinical Research in …, 2018
|Macrophage Exclusion after Radiation Therapy (MERT): A First in Human Phase I/II Trial using a CXCR4 Inhibitor in Glioblastoma|
RP Thomas, S Nagpal, M Iv, SG Soltys, S Bertrand, JS Pelpola, R Ball, ...
Clinical Cancer Research 25 (23), 6948-6957, 2019
|Radiology SWARM: novel crowdsourcing tool for CheXNet algorithm validation|
S Halabi, M Lungren, L Rosenberg, D Baltaxe, B Patel, J Seekins, ...
SiiM Conference on Machine Intelligence in Medical Imaging, 2018
|Predicting “Heart Age” Using Electrocardiography|
RL Ball, AH Feiveson, TT Schlegel, V Starc, AR Dabney
Journal of Personalized Medicine 4 (1), 65-78, 2014