RadGraph: Extracting Clinical Entities and Relations from Radiology Reports
Comments Accepted to the 35th Conference on Neural Information Processing Systems (NeurIPS 2021) Track on Datasets and Benchmarks
作者
Andrew Y. Ng
Machine Learning
Q-Pain: A Question Answering Dataset to Measure Social Bias in Pain Management
Comments Accepted to the 35th Conference on Neural Information Processing Systems (NeurIPS 2021) Track on Datasets and Benchmarks
CheXbreak: Misclassification Identification for Deep Learning Models Interpreting Chest X-rays
Comments In Proceedings of the 2021 Conference on Machine Learning for Health Care, 2021. In ACM Conference on Health, Inference, and Learning (ACM-CHIL) Workshop 2021
MoCo-CXR: MoCo Pretraining Improves Representation and Transferability of Chest X-ray Models
Comments Accepted at Medical Imaging with Deep Learning (MIDL) Conference 2021
CheXseen: Unseen Disease Detection for Deep Learning Interpretation of Chest X-rays
Comments Accepted at MIDL Conference 2021. Previous version accepted at ACM Conference on Health, Inference, and Learning (ACM-CHIL) Workshop 2021
CheXseg: Combining Expert Annotations with DNN-generated Saliency Maps for X-ray Segmentation
Comments Accepted to Medical Imaging with Deep Learning (MIDL) Conference 2021
Learning Neighborhood Representation from Multi-Modal Multi-Graph: Image, Text, Mobility Graph and Beyond
MedSelect: Selective Labeling for Medical Image Classification Combining Meta-Learning with Deep Reinforcement Learning
Evaluating the Disentanglement of Deep Generative Models through Manifold Topology
Comments Published at ICLR 2021
VisualCheXbert: Addressing the Discrepancy Between Radiology Report Labels and Image Labels
Comments Accepted to ACM Conference on Health, Inference, and Learning (ACM-CHIL) 2021
CheXternal: Generalization of Deep Learning Models for Chest X-ray Interpretation to Photos of Chest X-rays and External Clinical Settings
Comments Accepted to ACM Conference on Health, Inference, and Learning (ACM-CHIL) 2021. arXiv admin note: substantial text overlap with arXiv:2011.06129
CheXtransfer: Performance and Parameter Efficiency of ImageNet Models for Chest X-Ray Interpretation
CheXphoto: 10,000+ Photos and Transformations of Chest X-rays for Benchmarking Deep Learning Robustness
OGNet: Towards a Global Oil and Gas Infrastructure Database using Deep Learning on Remotely Sensed Imagery
Comments Tackling Climate Change with Machine Learning at NeurIPS 2020 (Spotlight talk)
CheXphotogenic: Generalization of Deep Learning Models for Chest X-ray Interpretation to Photos of Chest X-rays
Comments Machine Learning for Health (ML4H) at NeurIPS 2020 - Extended Abstract
GloFlow: Global Image Alignment for Creation of Whole Slide Images for Pathology from Video
Comments Machine Learning for Health (ML4H) at NeurIPS 2020 - Extended Abstract
ForestNet: Classifying Drivers of Deforestation in Indonesia using Deep Learning on Satellite Imagery
Comments Tackling Climate Change with Machine Learning at NeurIPS 2020
CheXbert: Combining Automatic Labelers and Expert Annotations for Accurate Radiology Report Labeling Using BERT
Comments Accepted to EMNLP 2020
Short-Term Solar Irradiance Forecasting Using Calibrated Probabilistic Models
DLBCL-Morph: Morphological features computed using deep learning for an annotated digital DLBCL image set
Comments Corrections to folder structure figure
NGBoost: Natural Gradient Boosting for Probabilistic Prediction
Comments Accepted for ICML 2020
Data augmentation with Mobius transformations
Effective Data Fusion with Generalized Vegetation Index: Evidence from Land Cover Segmentation in Agriculture
Comments CVPR 2020 - Vision for Agriculture; https://www.agriculture-vision.com
The 1st Agriculture-Vision Challenge: Methods and Results
Comments CVPR 2020 Workshop
CheXpedition: Investigating Generalization Challenges for Translation of Chest X-Ray Algorithms to the Clinical Setting
Comments Accepted as workshop paper at ACM Conference on Health, Inference, and Learning (CHIL) 2020
Deep Learning for the Digital Pathologic Diagnosis of Cholangiocarcinoma and Hepatocellular Carcinoma: Evaluating the Impact of a Web-based Diagnostic Assistant
Comments Machine Learning for Health (ML4H) at NeurIPS 2019 - Extended Abstract
Tackling Climate Change with Machine Learning
Comments For additional resources, please visit the website that accompanies this paper: https://www.climatechange.ai/
Countdown Regression: Sharp and Calibrated Survival Predictions
Comments UAI 2019
CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison
Comments Published in AAAI 2019
