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Volume 149: Machine Learning for Healthcare Conference, 6-7 August 2021, Virtual

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Editors: Ken Jung, Serena Yeung, Mark Sendak, Michael Sjoding, Rajesh Ranganath

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Model Selection for Offline Reinforcement Learning: Practical Considerations for Healthcare Settings

Shengpu Tang, Jenna Wiens; Proceedings of the 6th Machine Learning for Healthcare Conference, PMLR 149:2-35

Knowledge Graph-based Question Answering with Electronic Health Records

Junwoo Park, Youngwoo Cho, Haneol Lee, Jaegul Choo, Edward Choi; Proceedings of the 6th Machine Learning for Healthcare Conference, PMLR 149:36-53

Uncertainty-Aware Time-to-Event Prediction using Deep Kernel Accelerated Failure Time Models

Zhiliang Wu, Yinchong Yang, Peter A. Fashing, Volker Tresp; Proceedings of the 6th Machine Learning for Healthcare Conference, PMLR 149:54-79

Directing Human Attention in Event Localization for Clinical Timeline Creation

Jason Zhao, Monica Agrawal, Pedram Razavi, David Sontag; Proceedings of the 6th Machine Learning for Healthcare Conference, PMLR 149:80-102

CheXbreak: Misclassification Identification for Deep Learning Models Interpreting Chest X-rays

Emma Chen, Andy Kim, Rayan Krishnan, Jin Long, Andrew Y. Ng, Pranav Rajpurkar; Proceedings of the 6th Machine Learning for Healthcare Conference, PMLR 149:103-125

Understanding Clinical Collaborations Through Federated Classifier Selection

Sebastian Caldas, Joo Heung Yoon, Michael R. Pinsky, Gilles Clermont, Artur Dubrawski; Proceedings of the 6th Machine Learning for Healthcare Conference, PMLR 149:126-145

Deep Generative Analysis for Task-Based Functional MRI Experiments

Daniela de Albuquerque, Jack Goffinet, Rachael Wright, John Pearson; Proceedings of the 6th Machine Learning for Healthcare Conference, PMLR 149:146-175

Detecting Atrial Fibrillation in ICU Telemetry data with Weak Labels

Brian Chen, Golara Javadi, Amoon Jamzad, Alexander Hamilton, Stephanie Sibley, Purang Abolmaesumi, David Maslove, Parvin Mousavi; Proceedings of the 6th Machine Learning for Healthcare Conference, PMLR 149:176-195

Read, Attend, and Code: Pushing the Limits of Medical Codes Prediction from Clinical Notes by Machines

Byung-Hak Kim, Varun Ganapathi; Proceedings of the 6th Machine Learning for Healthcare Conference, PMLR 149:196-208

Power Constrained Bandits

Jiayu Yao, Emma Brunskill, Weiwei Pan, Susan Murphy, Finale Doshi-Velez; Proceedings of the 6th Machine Learning for Healthcare Conference, PMLR 149:209-259

EVA: Generating Longitudinal Electronic Health Records Using Conditional Variational Autoencoders

Siddharth Biswal, Soumya Ghosh, Jon Duke, Bradley Malin, Walter Stewart, Cao Xiao, Jimeng Sun; Proceedings of the 6th Machine Learning for Healthcare Conference, PMLR 149:260-282

Intraoperative Adverse Event Detection in Laparoscopic Surgery: Stabilized Multi-Stage Temporal Convolutional Network with Focal-Uncertainty Loss

Haiqi Wei, Frank Rudzicz, David Fleet, Teodor Grantcharov, Babak Taati; Proceedings of the 6th Machine Learning for Healthcare Conference, PMLR 149:283-307

Model-based metrics: Sample-efficient estimates of predictive model subpopulation performance

Andrew C. Miller, Leon A. Gatys, Joseph Futoma, Emily Fox; Proceedings of the 6th Machine Learning for Healthcare Conference, PMLR 149:308-336

An Interpretable Framework for Drug-Target Interaction with Gated Cross Attention

Yeachan Kim, Bonggun Shin; Proceedings of the 6th Machine Learning for Healthcare Conference, PMLR 149:337-353

Medically Aware GPT-3 as a Data Generator for Medical Dialogue Summarization

Bharath Chintagunta, Namit Katariya, Xavier Amatriain, Anitha Kannan; Proceedings of the 6th Machine Learning for Healthcare Conference, PMLR 149:354-372

Risk score learning for COVID-19 contact tracing apps

Kevin Murphy, Abhishek Kumar, Stylianos Serghiou; Proceedings of the 6th Machine Learning for Healthcare Conference, PMLR 149:373-390

MIMIC-SBDH: A Dataset for Social and Behavioral Determinants of Health

Hiba Ahsan, Emmie Ohnuki, Avijit Mitra, Hong You; Proceedings of the 6th Machine Learning for Healthcare Conference, PMLR 149:391-413

In-depth Benchmarking of Deep Neural Network Architectures for ECG Diagnosis

Naoki Nonaka, Jun Seita; Proceedings of the 6th Machine Learning for Healthcare Conference, PMLR 149:414-439

Hierarchical Information Criterion for Variable Abstraction

Mark Mirtchouk, Bharat Srikishan, Samantha Kleinberg; Proceedings of the 6th Machine Learning for Healthcare Conference, PMLR 149:440-460

Multi-Label Generalized Zero Shot Learning for the Classiffcation of Disease in Chest Radiographs

Nasir Hayat, Hazem Lashen, Farah E. Shamout; Proceedings of the 6th Machine Learning for Healthcare Conference, PMLR 149:461-477

Incorporating External Information in Tissue Subtyping: A Topic Modeling Approach

Ardvan Saeedi, Payman Yadollahpour, Sumedha Singla, Brian Pollack, William Wells, Frank Sciurba, Kayhan Batmanghelich; Proceedings of the 6th Machine Learning for Healthcare Conference, PMLR 149:478-505

Mind the Performance Gap: Examining Dataset Shift During Prospective Validation

Erkin Otles, Jeeheh Oh, Benjamin Li, Michelle Bochinski, Hyeon Joo, Justin Ortwine, Erica Shenoy, Laraine Washer, Vincent B. Young, Krishna Rao, Jenna Wiens; Proceedings of the 6th Machine Learning for Healthcare Conference, PMLR 149:506-534

A Generative Modeling Approach to Calibrated Predictions: A Use Case on Menstrual Cycle Length Prediction

Inigo Urteaga, Kathy Li, Amanda Shea, Virginia J. Vitzthum, Chris H. Wiggins, Noemie Elhadad; Proceedings of the 6th Machine Learning for Healthcare Conference, PMLR 149:535-566

Approximate Bayesian Computation for an Explicit-Duration Hidden Markov Model of COVID-19 Hospital Trajectories

Gian Marco Visani, Alexandra Hope Lee, Cuong Nguyen, David M. Kent, John B. Wong, Joshua T. Cohen, Michael C. Hughes; Proceedings of the 6th Machine Learning for Healthcare Conference, PMLR 149:567-613

A New Semi-supervised Learning Benchmark for Classifying View and Diagnosing Aortic Stenosis from Echocardiograms

Zhe Huang, Gary Long, Benjamin Wessler, Michael C. Hughes; Proceedings of the 6th Machine Learning for Healthcare Conference, PMLR 149:614-647

Dynamic Survival Analysis for EHR Data with Personalized Parametric Distributions

Preston Putzel, Hyungrok Do, Alex Boyd, Hua Zhong, Padhraic Smyth; Proceedings of the 6th Machine Learning for Healthcare Conference, PMLR 149:648-673

Deep Cox Mixtures for Survival Regression

Chirag Nagpal, Steve Yadlowsky, Negar Rostamzadeh, Katherine Heller; Proceedings of the 6th Machine Learning for Healthcare Conference, PMLR 149:674-708

Stool Image Analysis for Precision Health Monitoring by Smart Toilets

Jin Zhou, Nick DeCapite, Jackson McNabb, Jose R. Ruiz, Deborah A. Fisher, Sonia Grego, Krishnendu Chakrabarty; Proceedings of the 6th Machine Learning for Healthcare Conference, PMLR 149:709-729

Back to the basics with inclusion of clinical domain knowledge - A simple, scalable and effective model of Alzheimer’s Disease classification

Sarah C. Brüningk, Felix Hensel, Louis P. Lukas, Merel Kuijs, Catherine R. Jutzeler, Bastian Rieck; Proceedings of the 6th Machine Learning for Healthcare Conference, PMLR 149:730-754

MedAug: Contrastive learning leveraging patient metadata improves representations for chest X-ray interpretation

Yen Nhi Truong Vu, Richard Wang, Niranjan Balachandar, Can Liu, Andrew Y. Ng, Pranav Rajpurkar; Proceedings of the 6th Machine Learning for Healthcare Conference, PMLR 149:755-769

Point Processes for Competing Observations with Recurrent Networks (POPCORN): A Generative Model of EHR Data

Shreyas Bhave, Adler Perotte; Proceedings of the 6th Machine Learning for Healthcare Conference, PMLR 149:770-789

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