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

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

[bib][citeproc]

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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