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ORCIDMLHC 2021: Virtual Event
- Ken Jung, Serena Yeung, Mark P. Sendak, Michael W. Sjoding, Rajesh Ranganath:
Proceedings of the Machine Learning for Healthcare Conference, MLHC 2021, 6-7 August 2021, Virtual Event. Proceedings of Machine Learning Research 149, PMLR 2021 - Shengpu Tang
, Jenna Wiens:
Model Selection for Offline Reinforcement Learning: Practical Considerations for Healthcare Settings. 2-35 - Junwoo Park, Youngwoo Cho, Haneol Lee, Jaegul Choo, Edward Choi:
Knowledge Graph-based Question Answering with Electronic Health Records. 36-53 - Zhiliang Wu, Yinchong Yang, Peter A. Fasching, Volker Tresp:
Uncertainty-Aware Time-to-Event Prediction using Deep Kernel Accelerated Failure Time Models. 54-79 - Jason Zhao, Monica Agrawal, Pedram Razavi, David A. Sontag:
Directing Human Attention in Event Localization for Clinical Timeline Creation. 80-102 - Emma Chen, Andy Kim, Rayan Krishnan, Jin Long, Andrew Y. Ng, Pranav Rajpurkar:
CheXbreak: Misclassification Identification for Deep Learning Models Interpreting Chest X-rays. 103-125 - Sebastian Caldas, Joo Heung Yoon, Michael R. Pinsky, Gilles Clermont, Artur Dubrawski:
Understanding Clinical Collaborations Through Federated Classifier Selection. 126-145 - Daniela de Albuquerque, Jack Goffinet, Rachael Wright, John M. Pearson:
Deep Generative Analysis for Task-Based Functional MRI Experiments. 146-175 - Brian Chen, Golara Javadi, Amoon Jamzad, Alexander Hamilton, Stephanie Sibley, Purang Abolmaesumi, David Maslove, Parvin Mousavi:
Detecting Atrial Fibrillation in ICU Telemetry data with Weak Labels. 176-195 - Byung-Hak Kim, Varun Ganapathi:
Read, Attend, and Code: Pushing the Limits of Medical Codes Prediction from Clinical Notes by Machines. 196-208 - Jiayu Yao, Emma Brunskill, Weiwei Pan, Susan A. Murphy, Finale Doshi-Velez:
Power Constrained Bandits. 209-259 - Siddharth Biswal, Soumya Ghosh, Jon Duke, Bradley A. Malin, Walter F. Stewart, Cao Xiao, Jimeng Sun:
EVA: Generating Longitudinal Electronic Health Records Using Conditional Variational Autoencoders. 260-282 - Haiqi Wei, Frank Rudzicz, David Fleet, Teodor P. Grantcharov, Babak Taati:
Intraoperative Adverse Event Detection in Laparoscopic Surgery: Stabilized Multi-Stage Temporal Convolutional Network with Focal-Uncertainty Loss. 283-307 - Andrew C. Miller, Leon A. Gatys, Joseph Futoma, Emily B. Fox:
Model-based metrics: Sample-efficient estimates of predictive model subpopulation performance. 308-336 - Yeachan Kim, Bonggun Shin:
An Interpretable Framework for Drug-Target Interaction with Gated Cross Attention. 337-353 - Bharath Chintagunta, Namit Katariya, Xavier Amatriain, Anitha Kannan:
Medically Aware GPT-3 as a Data Generator for Medical Dialogue Summarization. 354-372 - Kevin Murphy, Abhishek Kumar, Stylianos Serghiou:
Risk score learning for COVID-19 contact tracing apps. 373-390 - Hiba Ahsan, Emmie Ohnuki, Avijit Mitra, Hong You:
MIMIC-SBDH: A Dataset for Social and Behavioral Determinants of Health. 391-413 - Naoki Nonaka, Jun Seita:
In-depth Benchmarking of Deep Neural Network Architectures for ECG Diagnosis. 414-439 - Mark Mirtchouk, Bharat Srikishan, Samantha Kleinberg:
Hierarchical Information Criterion for Variable Abstraction. 440-460 - Nasir Hayat, Hazem Lashen, Farah E. Shamout:
Multi-Label Generalized Zero Shot Learning for the Classiffcation of Disease in Chest Radiographs. 461-477 - Ardavan Saeedi, Payman Yadollahpour, Sumedha Singla, Brian Pollack, William M. Wells III, Frank C. Sciurba, Kayhan Batmanghelich:
Incorporating External Information in Tissue Subtyping: A Topic Modeling Approach. 478-505 - Erkin Ötles, Jeeheh Oh, Benjamin Li, Michelle Bochinski, Hyeon Joo, Justin Ortwine, Erica Shenoy, Laraine Washer, Vincent B. Young, Krishna Rao, Jenna Wiens:
Mind the Performance Gap: Examining Dataset Shift During Prospective Validation. 506-534 - Iñigo Urteaga, Kathy Li, Amanda Shea, Virginia J. Vitzthum, Chris H. Wiggins, Noemie Elhadad:
A Generative Modeling Approach to Calibrated Predictions: A Use Case on Menstrual Cycle Length Prediction. 535-566 - Gian Marco Visani, Alexandra Hope Lee, Cuong Nguyen, David M. Kent, John B. Wong, Joshua T. Cohen, Michael C. Hughes:
Approximate Bayesian Computation for an Explicit-Duration Hidden Markov Model of COVID-19 Hospital Trajectories. 567-613 - Zhe Huang, Gary Long, Benjamin Wessler, Michael C. Hughes:
A New Semi-supervised Learning Benchmark for Classifying View and Diagnosing Aortic Stenosis from Echocardiograms. 614-647 - Preston Putzel, Hyungrok Do, Alex Boyd, Hua Zhong, Padhraic Smyth:
Dynamic Survival Analysis for EHR Data with Personalized Parametric Distributions. 648-673 - Chirag Nagpal, Steve Yadlowsky, Negar Rostamzadeh, Katherine A. Heller:
Deep Cox Mixtures for Survival Regression. 674-708 - Jin Zhou, Nick DeCapite, Jackson McNabb, Jose R. Ruiz, Deborah A. Fisher, Sonia Grego, Krishnendu Chakrabarty:
Stool Image Analysis for Precision Health Monitoring by Smart Toilets. 709-729 - Sarah C. Brüningk, Felix Hensel, Louis P. Lukas, Merel Kuijs, Catherine R. Jutzeler, Bastian Rieck:
Back to the basics with inclusion of clinical domain knowledge - A simple, scalable and effective model of Alzheimer's Disease classification. 730-754 - Yen Nhi Truong Vu, Richard Wang, Niranjan Balachandar, Can Liu, Andrew Y. Ng, Pranav Rajpurkar:
MedAug: Contrastive learning leveraging patient metadata improves representations for chest X-ray interpretation. 755-769 - Shreyas Bhave, Adler J. Perotte:
Point Processes for Competing Observations with Recurrent Networks (POPCORN): A Generative Model of EHR Data. 770-789
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