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ORCIDML4H@NeurIPS 2021: Virtual Event
- Subhrajit Roy, Stephen Pfohl, Emma Rocheteau, Girmaw Abebe Tadesse, Luis Oala, Fabian Falck, Yuyin Zhou, Liyue Shen, Ghada Zamzmi, Purity Mugambi, Ayah Zirikly, Matthew B. A. McDermott, Emily Alsentzer:
Machine Learning for Health, ML4H@NeurIPS 2021, 04 December 2021, Virtual Event. Proceedings of Machine Learning Research 158, PMLR 2021 - Subhrajit Roy, Stephen Pfohl, Girmaw Abebe Tadesse, Luis Oala, Fabian Falck, Yuyin Zhou, Liyue Shen, Ghada Zamzmi, Purity Mugambi, Ayah Zirikly, Matthew B. A. McDermott, Emily Alsentzer:
Machine Learning for Health (ML4H) 2021. 1-12 - Seongsu Bae, Daeyoung Kim, Jiho Kim, Edward Choi:
Question Answering for Complex Electronic Health Records Database using Unified Encoder-Decoder Architecture. 13-25 - Jonathan Rubin, Ramon Erkamp, Ragha Srinivasa Naidu, Anumod Odungatta Thodiyil, Alvin Chen:
Attention Distillation for Detection Transformers: Application to Real-Time Video Object Detection in Ultrasound. 26-37 - Esther Dietrich, Patrick Fuhlert
, Anne Ernst, Guido Sauter, Maximilian Lennartz, H. Siegfried Stiehl, Marina Zimmermann, Stefan Bonn:
Towards Explainable End-to-End Prostate Cancer Relapse Prediction from H&E Images Combining Self-Attention Multiple Instance Learning with a Recurrent Neural Network. 38-53 - Tuan Truong, Sadegh Mohammadi, Matthias Lenga:
How Transferable are Self-supervised Features in Medical Image Classification Tasks? 54-74 - Ilya Valmianski, Nave Frost, Navdeep Sood, Yang Wang, Baodong Liu, James J. Zhu, Sunil Karumuri, Ian M. Finn, Daniel S. Zisook:
SmartTriage: A system for personalized patient data capture, documentation generation, and decision support. 75-96 - Danliang Ho, Iain Bee Huat Tan, Mehul Motani:
Prognosticating Colorectal Cancer Recurrence using an Interpretable Deep Multi-view Network. 97-109 - Rhys Compton, Ilya Valmianski, Li Deng, Costa Huang, Namit Katariya, Xavier Amatriain, Anitha Kannan:
MEDCOD: A Medically-Accurate, Emotive, Diverse, and Controllable Dialog System. 110-129 - Neeraj Wagh, Jionghao Wei, Samarth Rawal, Brent M. Berry, Leland Barnard, Benjamin H. Brinkmann, Gregory A. Worrell, David T. Jones, Yogatheesan Varatharajah:
Domain-guided Self-supervision of EEG Data Improves Downstream Classification Performance and Generalizability. 130-142 - Milan Kuzmanovic, Tobias Hatt, Stefan Feuerriegel:
Deconfounding Temporal Autoencoder: Estimating Treatment Effects over Time Using Noisy Proxies. 143-155 - Bryan Gopal, Ryan W. Han, Gautham Raghupathi, Andrew Y. Ng, Geoffrey H. Tison, Pranav Rajpurkar:
3KG: Contrastive Learning of 12-Lead Electrocardiograms using Physiologically-Inspired Augmentations. 156-167 - Peiqi Wang, Ruizhi Liao, Daniel Moyer, Seth J. Berkowitz, Steven Horng, Polina Golland:
Image Classification with Consistent Supporting Evidence. 168-180 - Lorena Qendro, Alexander Campbell, Pietro Liò, Cecilia Mascolo:
Early Exit Ensembles for Uncertainty Quantification. 181-195 - Ajay Jaiswal, Liyan Tang, Meheli Ghosh, Justin F. Rousseau, Yifan Peng, Ying Ding:
RadBERT-CL: Factually-Aware Contrastive Learning For Radiology Report Classification. 196-208 - Mark Endo, Rayan Krishnan, Viswesh Krishna, Andrew Y. Ng, Pranav Rajpurkar:
Retrieval-Based Chest X-Ray Report Generation Using a Pre-trained Contrastive Language-Image Model. 209-219 - Oliver Carr, Avelino Javer, Patrick Rockenschaub, Owen Parsons, Robert Dürichen:
Longitudinal patient stratification of electronic health records with flexible adjustment for clinical outcomes. 220-238 - Chao Pang, Xinzhuo Jiang, Krishna S. Kalluri, Matthew E. Spotnitz, Ruijun Chen, Adler J. Perotte, Karthik Natarajan:
CEHR-BERT: Incorporating temporal information from structured EHR data to improve prediction tasks. 239-260 - Tianwei Yin, Zihui Wu, He Sun, Adrian V. Dalca, Yisong Yue, Katherine L. Bouman:
End-to-End Sequential Sampling and Reconstruction for MRI. 261-281 - Rui Li, Stephanie M. Hu, Mingyu Lu, Yuria Utsumi, Prithwish Chakraborty, Daby M. Sow, Piyush Madan, Jun Li, Mohamed F. Ghalwash, Zach Shahn, Li-Wei H. Lehman:
G-Net: a Recurrent Network Approach to G-Computation for Counterfactual Prediction Under a Dynamic Treatment Regime. 282-299
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