| Transfer learning enables prediction of myocardial injury from continuous single-lead electrocardiography | 0 | 0.34 | 2022 |
| Contrastive learning of heart and lung sounds for label-efficient diagnosis | 0 | 0.34 | 2022 |
| Retrieval-Based Chest X-Ray Report Generation Using a Pre-trained Contrastive Language-Image Model. | 0 | 0.34 | 2021 |
| 3KG: Contrastive Learning of 12-Lead Electrocardiograms using Physiologically-Inspired Augmentations. | 0 | 0.34 | 2021 |
| CheXseg - Combining Expert Annotations with DNN-generated Saliency Maps for X-ray Segmentation. | 0 | 0.34 | 2021 |
| CheXbreak: Misclassification Identification for Deep Learning Models Interpreting Chest X-rays. | 0 | 0.34 | 2021 |
| GloFlow: Whole Slide Image Stitching from Video Using Optical Flow and Global Image Alignment | 0 | 0.34 | 2021 |
| Improving hospital readmission prediction using individualized utility analysis | 0 | 0.34 | 2021 |
| MedAug: Contrastive learning leveraging patient metadata improves representations for chest X-ray interpretation. | 0 | 0.34 | 2021 |
| CheXtransfer: Performance and Parameter Efficiency of ImageNet Models for Chest X-Ray Interpretation | 1 | 0.35 | 2021 |
| MoCo Pretraining Improves Representation and Transferability of Chest X-ray Models. | 0 | 0.34 | 2021 |
| VisualCheXbert: Addressing the Discrepancy Between Radiology Report Labels and Image Labels | 1 | 0.36 | 2021 |
| CheXternal: Generalization of Deep Learning Models for Chest X-ray Interpretation to Photos of Chest X-rays and External Clinical Settings | 0 | 0.34 | 2021 |
| RadGraph: Extracting Clinical Entities and Relations from Radiology Reports. | 0 | 0.34 | 2021 |
| CheXphoto: 10, 000+ Photos and Transformations of Chest X-rays for Benchmarking Deep Learning Robustness. | 0 | 0.34 | 2020 |
| Combining Automatic Labelers and Expert Annotations for Accurate Radiology Report Labeling Using BERT. | 0 | 0.34 | 2020 |
| CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison. | 10 | 0.56 | 2019 |
| Automated Abnormality Detection In Lower Extremity Radiographs Using Deep Learning | 0 | 0.34 | 2019 |
| Know What You Don'T Know: Unanswerable Questions For Squad | 24 | 0.72 | 2018 |
| MURA Dataset: Towards Radiologist-Level Abnormality Detection in Musculoskeletal Radiographs. | 4 | 0.41 | 2017 |
| Cardiologist-Level Arrhythmia Detection with Convolutional Neural Networks. | 36 | 1.68 | 2017 |
| Malaria Likelihood Prediction By Effectively Surveying Households Using Deep Reinforcement Learning. | 1 | 0.41 | 2017 |
| CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning. | 58 | 1.96 | 2017 |
| Augur: Mining Human Behaviors from Fiction to Power Interactive Systems. | 9 | 0.48 | 2016 |
| SQuAD: 100, 000+ Questions for Machine Comprehension of Text. | 365 | 10.41 | 2016 |
| Driverseat: Crowdstrapping Learning Tasks for Autonomous Driving | 2 | 0.35 | 2015 |
| An Empirical Evaluation of Deep Learning on Highway Driving. | 44 | 1.88 | 2015 |
| Text Mining Emergent Human Behaviors for Interactive Systems | 0 | 0.34 | 2015 |
