Pranav Rajpurkar
SQuAD: 100,000+ Questions for Machine Comprehension of Text
P Rajpurkar, J Zhang, K Lopyrev, P Liang
Proceedings of the 2016 Conference on Empirical Methods in Natural Language …, 2016
CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning
P Rajpurkar, J Irvin, K Zhu, B Yang, H Mehta, T Duan, D Ding, A Bagul, ...
arXiv preprint arXiv:1711.05225, 2017
Know What You Don't Know: Unanswerable Questions for SQuAD
P Rajpurkar, R Jia, P Liang
Proceedings of the 55th Annual Meeting of the Association for Computational …, 2018
Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network
AY Hannun, P Rajpurkar, M Haghpanahi, GH Tison, C Bourn, ...
Nature medicine 25 (1), 65-69, 2019
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, ...
Proceedings of the AAAI conference on artificial intelligence 33 (01), 590-597, 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
Cardiologist-Level Arrhythmia Detection with Convolutional Neural Networks
P Rajpurkar, AY Hannun, M Haghpanahi, C Bourn, AY Ng
arXiv preprint arXiv:1707.01836, 2017
An Empirical Evaluation of Deep Learning on Highway Driving
B Huval, T Wang, S Tandon, J Kiske, W Song, J Pazhayampallil, ...
arXiv preprint arXiv:1504.01716, 2015
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
AI in health and medicine
P Rajpurkar, E Chen, O Banerjee, EJ Topol
Nature Medicine 28 (1), 31-38, 2022
MURA: Large Dataset for Abnormality Detection in Musculoskeletal Radiographs
P Rajpurkar, J Irvin, A Bagul, D Ding, T Duan, H Mehta, B Yang, K Zhu, ...
1st Conference on Medical Imaging with Deep Learning, 2017
Deep Learning–Assisted Diagnosis of Cerebral Aneurysms Using the HeadXNet Model
A Park, C Chute, P Rajpurkar, J Lou, RL Ball, K Shpanskaya, ...
JAMA Network Open 2 (6), e195600-e195600, 2019
Impact of a deep learning assistant on the histopathologic classification of liver cancer
A Kiani, B Uyumazturk, P Rajpurkar, A Wang, R Gao, E Jones, Y Yu, ...
NPJ digital medicine 3 (1), 23, 2020
Human–machine partnership with artificial intelligence for chest radiograph diagnosis
BN Patel, L Rosenberg, G Willcox, D Baltaxe, M Lyons, J Irvin, ...
NPJ digital medicine 2 (1), 111, 2019
Moco pretraining improves representation and transferability of chest x-ray models
H Sowrirajan, J Yang, AY Ng, P Rajpurkar
Medical Imaging with Deep Learning, 728-744, 2021
CheXbert: Combining Automatic Labelers and Expert Annotations for Accurate Radiology Report Labeling Using BERT
A Smit, S Jain, P Rajpurkar, A Pareek, AY Ng, MP Lungren
Proceedings of the 2020 Conference on Empirical Methods in Natural Language …, 2020
CheXtransfer: Performance and Parameter Efficiency of ImageNet Models for Chest X-Ray Interpretation
A Ke, W Ellsworth, O Banerjee, AY Ng, P Rajpurkar
ACM Conference on Health, Inference, and Learning (ACM-CHIL) 2021, 2021
CheXaid: deep learning assistance for physician diagnosis of tuberculosis using chest x-rays in patients with HIV
P Rajpurkar, C O’Connell, A Schechter, N Asnani, J Li, A Kiani, RL Ball, ...
NPJ digital medicine 3 (1), 115, 2020
PENet—a scalable deep-learning model for automated diagnosis of pulmonary embolism using volumetric CT imaging
SC Huang, T Kothari, I Banerjee, C Chute, RL Ball, N Borus, A Huang, ...
NPJ digital medicine 3 (1), 61, 2020
AppendiXNet: deep learning for diagnosis of appendicitis from a small dataset of CT exams using video pretraining
P Rajpurkar, A Park, J Irvin, C Chute, M Bereket, D Mastrodicasa, ...
Scientific reports 10 (1), 3958, 2020
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Články 1–20