Volume 126: Machine Learning for Healthcare Conference, 7-8 August 2020, Virtual


Editors: Finale Doshi-Velez, Jim Fackler, Ken Jung, David Kale, Rajesh Ranganath, Byron Wallace, Jenna Wiens


Learning to Ask Medical Questions using Reinforcement Learning

Uri Shaham, Tom Zahavy, Cesar Caraballo, Shiwani Mahajan, Daisy Massey, Harlan Krumholz; PMLR 126:2-26

ScanMap: Supervised Confounding Aware Non-negative Matrix Factorization for Polygenic Risk Modeling

Yuan Luo, Chengsheng Mao; PMLR 126:27-45

An Evaluation of the Doctor-Interpretability of Generalized Additive Models with Interactions

Stefan Hegselmann, Thomas Volkert, Hendrik Ohlenburg, Antje Gottschalk, Martin Dugas, Christian Ertmer; PMLR 126:46-79

Towards Early Diagnosis of Epilepsy from EEG Data

Diyuan Lu, Sebastian Bauer, Valentin Neubert, Laura Sophie Costard, Felix Rosenow, Jochen Triesch; PMLR 126:80-96

Developing Personalized Models of Blood Pressure Estimation from Wearable Sensors Data Using Minimally-trained Domain Adversarial Neural Networks

Lida Zhang, Nathan C. Hurley, Bassem Ibrahim, Erica Spatz, Harlan M. Krumholz, Roozbeh Jafari, Mortazavi J. Bobak; PMLR 126:97-120

Optimizing Influenza Vaccine Composition: From Predictions to Prescriptions

Hari Bandi, Dimitris Bertsimas; PMLR 126:121-142

Towards data-driven stroke rehabilitation via wearable sensors and deep learning

Aakash Kaku, Avinash Parnandi, Anita Venkatesan, Natasha Pandit, Heidi Schambra, Carlos Fernandez-Granda; PMLR 126:143-171

Learning Insulin-Glucose Dynamics in the Wild

Andrew C. Miller, Nicholas J. Foti, Emily Fox; PMLR 126:172-197

Knowledge Base Completion for Constructing Problem-Oriented Medical Records

James Mullenbach, Jordan Swartz, T. Greg McKelvey, Hui Dai, David Sontag; PMLR 126:198-222

Neural Conditional Event Time Models

Matthew Engelhard, Samuel Berchuck, Joshua D’Arcy, Ricardo Henao; PMLR 126:223-244

Dynamically Extracting Outcome-Specific Problem Lists from Clinical Notes with Guided Multi-Headed Attention

Justin Lovelace, Nathan C. Hurley, Adrian D. Haimovich, Bobak J. Mortazavi; PMLR 126:245-270

Differentially Private Survival Function Estimation

Lovedeep Gondara, Ke Wang; PMLR 126:271-291

MRI-based Diagnosis of Rotator Cuff Tears using Deep Learning and Weighted Linear Combinations

Mijung Kim, Ho-min Park, Jae Yoon Kim, Seong Hwan Kim, Sofie Hoeke, Wesley De Neve; PMLR 126:292-308

Personalized Input-Output Hidden Markov Models for Disease Progression Modeling

Kristen A. Severson, Lana M. Chahine, Luba Smolensky, Kenney Ng, Jianying Hu, Soumya Ghosh; PMLR 126:309-330

Phenotyping with Prior Knowledge using Patient Similarity

Asif Rahman, Yale Chang, Bryan Conroy, Minnan Xu-Wilson; PMLR 126:331-351

Addressing Sample Size Challenges in Linked Data Through Data Fusion

Srikesh Arunajadai, Lulu Lee, Tom Haskell; PMLR 126:352-375

A Causally Formulated Hazard Ratio Estimation through Backdoor Adjustment on Structural Causal Model

Riddhiman Adib, Paul Griffin, Sheikh Iqbal Ahamed, Mohammad Adibuzzaman; PMLR 126:376-396

Comparisons Between Hamiltonian Monte Carlo and Maximum A Posteriori For A Bayesian Model For Apixaban Induction Dose & Dose Personalization

A. Demetri Pananos, Daniel J. Lizotte; PMLR 126:397-417

Evaluating and interpreting caption prediction for histopathology images

Renyu Zhang, Christopher Weber, Robert Grossman, Aly A. Khan; PMLR 126:418-435

Students Need More Attention: BERT-based Attention Model for Small Data with Application to Automatic Patient Message Triage

Shijing Si, Rui Wang, Jedrek Wosik, Hao Zhang, David Dov, Guoyin Wang, Lawrence Carin; PMLR 126:436-456

Attentive Adversarial Network for Large-Scale Sleep Staging

Samaneh Nasiri, Gari D. Clifford; PMLR 126:457-478

Attention-Based Network for Weak Labels in Neonatal Seizure Detection

Dmitry Yu. Isaev, Dmitry Tchapyjnikov, C. Michael Cotten, David Tanaka, Natalia Martinez, Martin Bertran, Guillermo Sapiro, David Carlson; PMLR 126:479-507

Deep Reinforcement Learning for Closed-Loop Blood Glucose Control

Ian Fox, Joyce Lee, Rodica Pop-Busui, Jenna Wiens; PMLR 126:508-536

Deep Kernel Survival Analysis and Subject-Specific Survival Time Prediction Intervals

George H. Chen; PMLR 126:537-565

Time-Aware Transformer-based Network for Clinical Notes Series Prediction

Dongyu Zhang, Jidapa Thadajarassiri, Cansu Sen, Elke Rundensteiner; PMLR 126:566-588

Transfer Learning from Well-Curated to Less-Resourced Populations with HIV

Sonali Parbhoo, Mario Wieser, Volker Roth, Finale Doshi-Velez; PMLR 126:589-609

Towards an Automated SOAP Note: Classifying Utterances from Medical Conversations

Benjamin Schloss, Sandeep Konam; PMLR 126:610-631

Query-Focused EHR Summarization to Aid Imaging Diagnosis

Denis Jered McInerney, Borna Dabiri, Anne-Sophie Touret, Geoffrey Young, Jan-Willem Meent, Byron C. Wallace; PMLR 126:632-659

Predicting Drug Sensitivity of Cancer Cell Lines via Collaborative Filtering with Contextual Attention

Yifeng Tao, Shuangxia Ren, Michael Q. Ding, Russell Schwartz, Xinghua Lu; PMLR 126:660-684

Using deep networks for scientific discovery in physiological signals

Tom Beer, Bar Eini-Porat, Sebastian Goodfellow, Danny Eytan, Uri Shalit; PMLR 126:685-709

Hidden Risks of Machine Learning Applied to Healthcare: Unintended Feedback Loops Between Models and Future Data Causing Model Degradation

George Alexandru Adam, Chun-Hao Kingsley Chang, Benjamin Haibe-Kains, Anna Goldenberg; PMLR 126:710-731

Self-Supervised Pretraining with DICOM metadata in Ultrasound Imaging

Szu-Yen Hu, Shuhang Wang, Wei-Hung Weng, JingChao Wang, XiaoHong Wang, Arinc Ozturk, Quan Li, Viksit Kumar, Anthony E. Samir; PMLR 126:732-749

Deep Learning Applied to Chest X-Rays: Exploiting and Preventing Shortcuts

Sarah Jabbour, David Fouhey, Ella Kazerooni, Michael W. Sjoding, Jenna Wiens; PMLR 126:750-782

Clinical Collabsheets: 53 Questions to Guide a Clinical Collaboration

Shems Saleh, William Boag, Lauren Erdman, Tristan Naumann; PMLR 126:783-812

Non-Invasive Classification of Alzheimer’s Disease Using Eye Tracking and Language

Oswald Barral, Hyeju Jang, Sally Newton-Mason, Sheetal Shajan, Thomas Soroski, Giuseppe Carenini, Cristina Conati, Thalia Field; PMLR 126:813-841

Fast, Structured Clinical Documentation via Contextual Autocomplete

Divya Gopinath, Monica Agrawal, Luke Murray, Steven Horng, David Karger, David Sontag; PMLR 126:842-870

Comparing Machine Learning Techniques for Blood Glucose Forecasting Using Free-living and Patient Generated Data

Hadia Hameed, Samantha Kleinberg; PMLR 126:871-894

UPSTAGE: Unsupervised Context Augmentation for Utterance Classification in Patient-Provider Communication

Do June Min, Veronica Perez-Rosas, Shihchen Kuo, William H. Herman, Rada Mihalcea; PMLR 126:895-912

CheXpert++: Approximating the CheXpert Labeler for Speed, Differentiability, and Probabilistic Output

Matthew B.A. McDermott, Tzu Ming Harry Hsu, Wei-Hung Weng, Marzyeh Ghassemi, Peter Szolovits; PMLR 126:913-927

Robust Benchmarking for Machine Learning of Clinical Entity Extraction

Monica Agrawal, Chloe O’Connell, Yasmin Fatemi, Ariel Levy, David Sontag; PMLR 126:928-949

Preparing a Clinical Support Model for Silent Mode in General Internal Medicine

Bret Nestor, Liam G. McCoy, Amol Verma, Chloe Pou-Prom, Joshua Murray, Sebnem Kuzulugil, David Dai, Muhammad Mamdani, Anna Goldenberg; PMLR 126:950-972

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