Abstract is missing.
- Model Selection for Offline Reinforcement Learning: Practical Considerations for Healthcare SettingsShengpu Tang, Jenna Wiens. 2-35 [doi]
- Knowledge Graph-based Question Answering with Electronic Health RecordsJunwoo Park, Youngwoo Cho, Haneol Lee, Jaegul Choo, Edward Choi. 36-53 [doi]
- Uncertainty-Aware Time-to-Event Prediction using Deep Kernel Accelerated Failure Time ModelsZhiliang Wu, Yinchong Yang, Peter A. Fasching, Volker Tresp. 54-79 [doi]
- Directing Human Attention in Event Localization for Clinical Timeline CreationJason Zhao, Monica Agrawal, Pedram Razavi, David A. Sontag. 80-102 [doi]
- CheXbreak: Misclassification Identification for Deep Learning Models Interpreting Chest X-raysEmma Chen, Andy Kim, Rayan Krishnan, Jin-long, Andrew Y. Ng, Pranav Rajpurkar. 103-125 [doi]
- Understanding Clinical Collaborations Through Federated Classifier SelectionSebastian Caldas, Joo Heung Yoon, Michael R. Pinsky, Gilles Clermont, Artur Dubrawski. 126-145 [doi]
- Deep Generative Analysis for Task-Based Functional MRI ExperimentsDaniela de Albuquerque, Jack Goffinet, Rachael Wright, John Pearson. 146-175 [doi]
- Detecting Atrial Fibrillation in ICU Telemetry data with Weak LabelsBrian Chen, Golara Javadi, Amoon Jamzad, Alexander Hamilton, Stephanie Sibley, Purang Abolmaesumi, David Maslove, Parvin Mousavi. 176-195 [doi]
- Read, Attend, and Code: Pushing the Limits of Medical Codes Prediction from Clinical Notes by MachinesByung-Hak Kim, Varun Ganapathi. 196-208 [doi]
- Power Constrained BanditsJiayu Yao, Emma Brunskill, Weiwei Pan, Susan A. Murphy, Finale Doshi-Velez. 209-259 [doi]
- EVA: Generating Longitudinal Electronic Health Records Using Conditional Variational AutoencodersSiddharth Biswal, Soumya Ghosh, Jon Duke, Bradley A. Malin, Walter F. Stewart, Cao Xiao, Jimeng Sun. 260-282 [doi]
- Intraoperative Adverse Event Detection in Laparoscopic Surgery: Stabilized Multi-Stage Temporal Convolutional Network with Focal-Uncertainty LossHaiqi Wei, Frank Rudzicz, David Fleet, Teodor P. Grantcharov, Babak Taati. 283-307 [doi]
- Model-based metrics: Sample-efficient estimates of predictive model subpopulation performanceAndrew C. Miller, Leon A. Gatys, Joseph Futoma, Emily B. Fox. 308-336 [doi]
- An Interpretable Framework for Drug-Target Interaction with Gated Cross AttentionYeachan Kim, Bonggun Shin. 337-353 [doi]
- Medically Aware GPT-3 as a Data Generator for Medical Dialogue SummarizationBharath Chintagunta, Namit Katariya, Xavier Amatriain, Anitha Kannan. 354-372 [doi]
- Risk score learning for COVID-19 contact tracing appsKevin Murphy 0002, Abhishek Kumar, Stylianos Serghiou. 373-390 [doi]
- MIMIC-SBDH: A Dataset for Social and Behavioral Determinants of HealthHiba Ahsan, Emmie Ohnuki, Avijit Mitra, Hong You. 391-413 [doi]
- In-depth Benchmarking of Deep Neural Network Architectures for ECG DiagnosisNaoki Nonaka, Jun Seita. 414-439 [doi]
- Hierarchical Information Criterion for Variable AbstractionMark Mirtchouk, Bharat Srikishan, Samantha Kleinberg. 440-460 [doi]
- Multi-Label Generalized Zero Shot Learning for the Classiffcation of Disease in Chest RadiographsNasir Hayat, Hazem Lashen, Farah E. Shamout. 461-477 [doi]
- Incorporating External Information in Tissue Subtyping: A Topic Modeling ApproachArdavan Saeedi, Payman Yadollahpour, Sumedha Singla, Brian Pollack, William M. Wells III, Frank C. Sciurba, Kayhan Batmanghelich. 478-505 [doi]
- Mind the Performance Gap: Examining Dataset Shift During Prospective ValidationErkin Ötles, Jeeheh Oh, Benjamin Li, Michelle Bochinski, Hyeon Joo, Justin Ortwine, Erica Shenoy, Laraine Washer, Vincent B. Young, Krishna Rao, Jenna Wiens. 506-534 [doi]
- A Generative Modeling Approach to Calibrated Predictions: A Use Case on Menstrual Cycle Length PredictionIñigo Urteaga, Kathy Li, Amanda Shea, Virginia J. Vitzthum, Chris H. Wiggins, Noemie Elhadad. 535-566 [doi]
- Approximate Bayesian Computation for an Explicit-Duration Hidden Markov Model of COVID-19 Hospital TrajectoriesGian Marco Visani, Alexandra Hope Lee, Cuong Nguyen, David M. Kent, John B. Wong, Joshua T. Cohen, Michael C. Hughes. 567-613 [doi]
- A New Semi-supervised Learning Benchmark for Classifying View and Diagnosing Aortic Stenosis from EchocardiogramsZhe Huang, Gary Long, Benjamin Wessler, Michael C. Hughes. 614-647 [doi]
- Dynamic Survival Analysis for EHR Data with Personalized Parametric DistributionsPreston Putzel, Hyungrok Do, Alex Boyd, Hua Zhong, Padhraic Smyth. 648-673 [doi]
- Deep Cox Mixtures for Survival RegressionChirag Nagpal, Steve Yadlowsky, Negar Rostamzadeh, Katherine A. Heller. 674-708 [doi]
- Stool Image Analysis for Precision Health Monitoring by Smart ToiletsJin Zhou, Nick DeCapite, Jackson McNabb, Jose R. Ruiz, Deborah A. Fisher, Sonia Grego, Krishnendu Chakrabarty. 709-729 [doi]
- Back to the basics with inclusion of clinical domain knowledge - A simple, scalable and effective model of Alzheimer's Disease classificationSarah C. Brüningk, Felix Hensel, Louis P. Lukas, Merel Kuijs, Catherine R. Jutzeler, Bastian Rieck. 730-754 [doi]
- MedAug: Contrastive learning leveraging patient metadata improves representations for chest X-ray interpretationYen Nhi Truong Vu, Richard Wang, Niranjan Balachandar, Can Liu, Andrew Y. Ng, Pranav Rajpurkar. 755-769 [doi]
- Point Processes for Competing Observations with Recurrent Networks (POPCORN): A Generative Model of EHR DataShreyas Bhave, Adler J. Perotte. 770-789 [doi]