MLHC 2021

31 papers

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

Shreyas Bhave, Adler Perotte

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

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

Stool Image Analysis for Precision Health Monitoring by Smart Toilets

Jin Zhou, Nick DeCapite, Jackson McNabb, Jose R. Ruiz, Deborah A. Fisher

Deep Cox Mixtures for Survival Regression

Chirag Nagpal, Steve Yadlowsky, Negar Rostamzadeh, Katherine Heller

Dynamic Survival Analysis for EHR Data with Personalized Parametric Distributions

Preston Putzel, Hyungrok Do, Alex Boyd, Hua Zhong, Padhraic Smyth

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

Zhe Huang, Gary Long, Benjamin Wessler, Michael C. Hughes

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

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

Mind the Performance Gap: Examining Dataset Shift During Prospective Validation

Erkin Otles, Jeeheh Oh, Benjamin Li, Michelle Bochinski, Hyeon Joo

Incorporating External Information in Tissue Subtyping: A Topic Modeling Approach

Ardvan Saeedi, Payman Yadollahpour, Sumedha Singla, Brian Pollack, William Wells

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

Nasir Hayat, Hazem Lashen, Farah E. Shamout

Hierarchical Information Criterion for Variable Abstraction

Mark Mirtchouk, Bharat Srikishan, Samantha Kleinberg

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

Naoki Nonaka, Jun Seita

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

Hiba Ahsan, Emmie Ohnuki, Avijit Mitra, Hong You

Risk score learning for COVID-19 contact tracing apps

Kevin Murphy, Abhishek Kumar, Stylianos Serghiou

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

Bharath Chintagunta, Namit Katariya, Xavier Amatriain, Anitha Kannan

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

Yeachan Kim, Bonggun Shin

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

Andrew C. Miller, Leon A. Gatys, Joseph Futoma, Emily Fox

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

EVA: Generating Longitudinal Electronic Health Records Using Conditional Variational Autoencoders

Siddharth Biswal, Soumya Ghosh, Jon Duke, Bradley Malin, Walter Stewart

Power Constrained Bandits

Jiayu Yao, Emma Brunskill, Weiwei Pan, Susan Murphy, Finale Doshi-velez

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

Byung-Hak Kim, Varun Ganapathi

Detecting Atrial Fibrillation in ICU Telemetry data with Weak Labels

Brian Chen, Golara Javadi, Amoon Jamzad, Alexander Hamilton, Stephanie Sibley

Deep Generative Analysis for Task-Based Functional MRI Experiments

Daniela de Albuquerque, Jack Goffinet, Rachael Wright, John Pearson

Understanding Clinical Collaborations Through Federated Classifier Selection

Sebastian Caldas, Joo Heung Yoon, Michael R. Pinsky, Gilles Clermont, Artur Dubrawski

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

Emma Chen, Andy Kim, Rayan Krishnan, Jin Long, Andrew Y. Ng

Directing Human Attention in Event Localization for Clinical Timeline Creation

Jason Zhao, Monica Agrawal, Pedram Razavi, David Sontag

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

Zhiliang Wu, Yinchong Yang, Peter A. Fashing, Volker Tresp

Knowledge Graph-based Question Answering with Electronic Health Records

Junwoo Park, Youngwoo Cho, Haneol Lee, Jaegul Choo, Edward Choi

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

Shengpu Tang, Jenna Wiens