MLHC 2020

41 papers

A Causally Formulated Hazard Ratio Estimation Through Backdoor Adjustment on Structural Causal Model Riddhiman Adib, Paul Griffin, Sheikh Iqbal Ahamed, Mohammad Adibuzzaman

Addressing Sample Size Challenges in Linked Data Through Data Fusion Srikesh Arunajadai, Lulu Lee, Tom Haskell

An Evaluation of the Doctor-Interpretability of Generalized Additive Models with Interactions Stefan Hegselmann, Thomas Volkert, Hendrik Ohlenburg, Antje Gottschalk, Martin Dugas, Christian Ertmer

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

Attentive Adversarial Network for Large-Scale Sleep Staging Samaneh Nasiri, Gari D. Clifford

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

Clinical Collabsheets: 53 Questions to Guide a Clinical Collaboration Shems Saleh, William Boag, Lauren Erdman, Tristan Naumann

Comparing Machine Learning Techniques for Blood Glucose Forecasting Using Free-Living and Patient Generated Data Hadia Hameed, Samantha Kleinberg

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

Deep Kernel Survival Analysis and Subject-Specific Survival Time Prediction Intervals George H. Chen

Deep Learning Applied to Chest X-Rays: Exploiting and Preventing Shortcuts Sarah Jabbour, David Fouhey, Ella Kazerooni, Michael W. Sjoding, Jenna Wiens

Deep Reinforcement Learning for Closed-Loop Blood Glucose Control Ian Fox, Joyce Lee, Rodica Pop-Busui, Jenna Wiens

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

Differentially Private Survival Function Estimation Lovedeep Gondara, Ke Wang

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

Evaluating and Interpreting Caption Prediction for Histopathology Images Renyu Zhang, Christopher Weber, Robert Grossman, Aly A. Khan

Fast, Structured Clinical Documentation via Contextual Autocomplete Divya Gopinath, Monica Agrawal, Luke Murray, Steven Horng, David Karger, David Sontag

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

Knowledge Base Completion for Constructing Problem-Oriented Medical Records James Mullenbach, Jordan Swartz, T. Greg McKelvey, Hui Dai, David Sontag

Learning Insulin-Glucose Dynamics in the Wild Andrew C. Miller, Nicholas J. Foti, Emily Fox

Learning to Ask Medical Questions Using Reinforcement Learning Uri Shaham, Tom Zahavy, Cesar Caraballo, Shiwani Mahajan, Daisy Massey, Harlan Krumholz

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

Neural Conditional Event Time Models Matthew Engelhard, Samuel Berchuck, Joshua D’Arcy, Ricardo Henao

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

Optimizing Influenza Vaccine Composition: From Predictions to Prescriptions Hari Bandi, Dimitris Bertsimas

Personalized Input-Output Hidden Markov Models for Disease Progression Modeling Kristen A. Severson, Lana M. Chahine, Luba Smolensky, Kenney Ng, Jianying Hu, Soumya Ghosh

Phenotyping with Prior Knowledge Using Patient Similarity Asif Rahman, Yale Chang, Bryan Conroy, Minnan Xu-Wilson

Predicting Drug Sensitivity of Cancer Cell Lines via Collaborative Filtering with Contextual Attention Yifeng Tao, Shuangxia Ren, Michael Q. Ding, Russell Schwartz, Xinghua Lu

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, Marzyeh Ghassemi

Query-Focused EHR Summarization to Aid Imaging Diagnosis Denis Jered McInerney, Borna Dabiri, Anne-Sophie Touret, Geoffrey Young, Jan-Willem Meent, Byron C. Wallace

Robust Benchmarking for Machine Learning of Clinical Entity Extraction Monica Agrawal, Chloe O’Connell, Yasmin Fatemi, Ariel Levy, David Sontag

ScanMap: Supervised Confounding Aware Non-Negative Matrix Factorization for Polygenic Risk Modeling Yuan Luo, Chengsheng Mao

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

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

Time-Aware Transformer-Based Network for Clinical Notes Series Prediction Dongyu Zhang, Jidapa Thadajarassiri, Cansu Sen, Elke Rundensteiner

Towards an Automated SOAP Note: Classifying Utterances from Medical Conversations Benjamin Schloss, Sandeep Konam

Towards Data-Driven Stroke Rehabilitation via Wearable Sensors and Deep Learning Aakash Kaku, Avinash Parnandi, Anita Venkatesan, Natasha Pandit, Heidi Schambra, Carlos Fernandez-Granda

Towards Early Diagnosis of Epilepsy from EEG Data Diyuan Lu, Sebastian Bauer, Valentin Neubert, Laura Sophie Costard, Felix Rosenow, Jochen Triesch

Transfer Learning from Well-Curated to Less-Resourced Populations with HIV Sonali Parbhoo, Mario Wieser, Volker Roth, Finale Doshi-Velez

UPSTAGE: Unsupervised Context Augmentation for Utterance Classification in Patient-Provider Communication Do June Min, Veronica Perez-Rosas, Shihchen Kuo, William H. Herman, Rada Mihalcea

Using Deep Networks for Scientific Discovery in Physiological Signals Tom Beer, Bar Eini-Porat, Sebastian Goodfellow, Danny Eytan, Uri Shalit