Machine Learning for Health (ML4H) 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; Proceedings of Machine Learning for Health, PMLR 158:1-12

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Question Answering for Complex Electronic Health Records Database using Unified Encoder-Decoder Architecture

Seongsu Bae, Daeyoung Kim, Jiho Kim, Edward Choi; Proceedings of Machine Learning for Health, PMLR 158:13-25

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Attention Distillation for Detection Transformers: Application to Real-Time Video Object Detection in Ultrasound

Jonathan Rubin, Ramon Erkamp, Ragha Srinivasa Naidu, Anumod Odungatta Thodiyil, Alvin Chen; Proceedings of Machine Learning for Health, PMLR 158:26-37

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Towards Explainable End-to-End Prostate Cancer Relapse Prediction from H&E Images Combining Self-Attention Multiple Instance Learning with a Recurrent Neural Network

Esther Dietrich, Patrick Fuhlert, Anne Ernst, Guido Sauter, Maximilian Lennartz, H. Siegfried Stiehl, Marina Zimmermann, Stefan Bonn; Proceedings of Machine Learning for Health, PMLR 158:38-53

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How Transferable are Self-supervised Features in Medical Image Classification Tasks?

Tuan Truong, Sadegh Mohammadi, Matthias Lenga; Proceedings of Machine Learning for Health, PMLR 158:54-74

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SmartTriage: A system for personalized patient data capture, documentation generation, and decision support

Ilya Valmianski, Nave Frost, Navdeep Sood, Yang Wang, Baodong Liu, James J. Zhu, Sunil Karumuri, Ian M. Finn, Daniel S. Zisook; Proceedings of Machine Learning for Health, PMLR 158:75-96

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Prognosticating Colorectal Cancer Recurrence using an Interpretable Deep Multi-view Network

Danliang Ho, Iain Bee Huat Tan, Mehul Motani; Proceedings of Machine Learning for Health, PMLR 158:97-109

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MEDCOD: A Medically-Accurate, Emotive, Diverse, and Controllable Dialog System

Rhys Compton, Ilya Valmianski, Li Deng, Costa Huang, Namit Katariya, Xavier Amatriain, Anitha Kannan; Proceedings of Machine Learning for Health, PMLR 158:110-129

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Domain-guided Self-supervision of EEG Data Improves Downstream Classification Performance and Generalizability

Neeraj Wagh, Jionghao Wei, Samarth Rawal, Brent Berry, Leland Barnard, Benjamin Brinkmann, Gregory Worrell, David Jones, Yogatheesan Varatharajah; Proceedings of Machine Learning for Health, PMLR 158:130-142

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Deconfounding Temporal Autoencoder: Estimating Treatment Effects over Time Using Noisy Proxies

Milan Kuzmanovic, Tobias Hatt, Stefan Feuerriegel; Proceedings of Machine Learning for Health, PMLR 158:143-155

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3KG: Contrastive Learning of 12-Lead Electrocardiograms using Physiologically-Inspired Augmentations

Bryan Gopal, Ryan Han, Gautham Raghupathi, Andrew Ng, Geoff Tison, Pranav Rajpurkar; Proceedings of Machine Learning for Health, PMLR 158:156-167

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Image Classification with Consistent Supporting Evidence

Peiqi Wang, Ruizhi Liao, Daniel Moyer, Seth Berkowitz, Steven Horng, Polina Golland; Proceedings of Machine Learning for Health, PMLR 158:168-180

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Early Exit Ensembles for Uncertainty Quantification

Lorena Qendro, Alexander Campbell, Pietro Lio, Cecilia Mascolo; Proceedings of Machine Learning for Health, PMLR 158:181-195

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RadBERT-CL: Factually-Aware Contrastive Learning For Radiology Report Classification

Ajay Jaiswal, Liyan Tang, Meheli Ghosh, Justin F. Rousseau, Yifan Peng, Ying Ding; Proceedings of Machine Learning for Health, PMLR 158:196-208

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Retrieval-Based Chest X-Ray Report Generation Using a Pre-trained Contrastive Language-Image Model

Mark Endo, Rayan Krishnan, Viswesh Krishna, Andrew Y. Ng, Pranav Rajpurkar; Proceedings of Machine Learning for Health, PMLR 158:209-219

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Longitudinal patient stratification of electronic health records with flexible adjustment for clinical outcomes

Oliver Carr, Avelino Javer, Patrick Rockenschaub, Owen Parsons, Robert Durichen; Proceedings of Machine Learning for Health, PMLR 158:220-238

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CEHR-BERT: Incorporating temporal information from structured EHR data to improve prediction tasks

Chao Pang, Xinzhuo Jiang, Krishna S. Kalluri, Matthew Spotnitz, RuiJun Chen, Adler Perotte, Karthik Natarajan; Proceedings of Machine Learning for Health, PMLR 158:239-260

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End-to-End Sequential Sampling and Reconstruction for MRI

Tianwei Yin, Zihui Wu, He Sun, Adrian V. Dalca, Yisong Yue, Katherine L. Bouman; Proceedings of Machine Learning for Health, PMLR 158:261-281

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G-Net: a Recurrent Network Approach to G-Computation for Counterfactual Prediction Under a Dynamic Treatment Regime

Rui Li, Stephanie Hu, Mingyu Lu, Yuria Utsumi, Prithwish Chakraborty, Daby M. Sow, Piyush Madan, Jun Li, Mohamed Ghalwash, Zach Shahn, Li-wei Lehman; Proceedings of Machine Learning for Health, PMLR 158:282-299

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