Abstract is missing.
- Learning to Ask Medical Questions using Reinforcement LearningUri Shaham, Tom Zahavy, Cesar Caraballo, Shiwani Mahajan, Daisy Massey, Harlan M. Krumholz. 2-26 [doi]
- ScanMap: Supervised Confounding Aware Non-negative Matrix Factorization for Polygenic Risk ModelingYuan Luo 0004, Chengsheng Mao. 27-45 [doi]
- An Evaluation of the Doctor-Interpretability of Generalized Additive Models with InteractionsStefan Hegselmann, Thomas Volkert, Hendrik Ohlenburg, Antje Gottschalk, Martin Dugas, Christian Ertmer. 46-79 [doi]
- Towards Early Diagnosis of Epilepsy from EEG DataDiyuan Lu, Sebastian Bauer, Valentin Neubert, Lara Sophie Costard, Felix Rosenow, Jochen Triesch. 80-96 [doi]
- Developing Personalized Models of Blood Pressure Estimation from Wearable Sensors Data Using Minimally-trained Domain Adversarial Neural NetworksLida Zhang, Nathan C. Hurley, Bassem Ibrahim, Erica S. Spatz, Harlan M. Krumholz, Roozbeh Jafari, Bobak Jack Mortazavi. 97-120 [doi]
- Optimizing Influenza Vaccine Composition: From Predictions to PrescriptionsHari Bandi, Dimitris Bertsimas. 121-142 [doi]
- Towards data-driven stroke rehabilitation via wearable sensors and deep learningAakash Kaku, Avinash Parnandi, Anita Venkatesan, Natasha Pandit, Heidi M. Schambra, Carlos Fernandez-Granda. 143-171 [doi]
- Learning Insulin-Glucose Dynamics in the WildAndrew C. Miller, Nicholas J. Foti, Emily B. Fox. 172-197 [doi]
- Knowledge Base Completion for Constructing Problem-Oriented Medical RecordsJames Mullenbach, Jordan Swartz, T. Greg McKelvey, Hui Dai, David A. Sontag. 198-222 [doi]
- Neural Conditional Event Time ModelsMatthew Engelhard, Samuel Berchuck, Joshua D'Arcy, Ricardo Henao. 223-244 [doi]
- Dynamically Extracting Outcome-Specific Problem Lists from Clinical Notes with Guided Multi-Headed AttentionJustin R. Lovelace, Nathan C. Hurley, Adrian D. Haimovich, Bobak J. Mortazavi. 245-270 [doi]
- Differentially Private Survival Function EstimationLovedeep Gondara, Ke Wang 0001. 271-291 [doi]
- MRI-based Diagnosis of Rotator Cuff Tears using Deep Learning and Weighted Linear CombinationsMijung Kim, Ho-min Park, Jae Yoon Kim, Seong-Hwan Kim, Sofie Hoeke, Wesley De Neve. 292-308 [doi]
- Personalized Input-Output Hidden Markov Models for Disease Progression ModelingKristen A. Severson, Lana M. Chahine, Luba Smolensky, Kenney Ng, Jianying Hu, Soumya Ghosh. 309-330 [doi]
- Phenotyping with Prior Knowledge using Patient SimilarityAsif Rahman, Yale Chang, Bryan Conroy, Minnan Xu-Wilson. 331-351 [doi]
- Addressing Sample Size Challenges in Linked Data Through Data FusionSrikesh Arunajadai, Lulu Lee, Tom Haskell. 352-375 [doi]
- A Causally Formulated Hazard Ratio Estimation through Backdoor Adjustment on Structural Causal ModelRiddhiman Adib, Paul M. Griffin, Sheikh Iqbal Ahamed, Mohammad Adibuzzaman. 376-396 [doi]
- Comparisons Between Hamiltonian Monte Carlo and Maximum A Posteriori For A Bayesian Model For Apixaban Induction Dose & Dose PersonalizationA. Demetri Pananos, Daniel J. Lizotte. 397-417 [doi]
- Evaluating and interpreting caption prediction for histopathology imagesRenyu Zhang, Christopher Weber, Robert Grossman, Aly A. Khan. 418-435 [doi]
- Students Need More Attention: BERT-based Attention Model for Small Data with Application to Automatic Patient Message TriageShijing Si, Rui Wang, Jedrek Wosik, Hao Zhang, David Dov, Guoyin Wang 0002, Lawrence Carin. 436-456 [doi]
- Attentive Adversarial Network for Large-Scale Sleep StagingSamaneh Nasiri, Gari D. Clifford. 457-478 [doi]
- Attention-Based Network for Weak Labels in Neonatal Seizure DetectionDmitry Yu. Isaev, Dmitry Tchapyjnikov, C. Michael Cotten, David Tanaka, Natalia Martínez, Martín Bertrán, Guillermo Sapiro, David Carlson. 479-507 [doi]
- Deep Reinforcement Learning for Closed-Loop Blood Glucose ControlIan Fox, Joyce Lee, Rodica Pop-Busui, Jenna Wiens. 508-536 [doi]
- Deep Kernel Survival Analysis and Subject-Specific Survival Time Prediction IntervalsGeorge H. Chen. 537-565 [doi]
- Time-Aware Transformer-based Network for Clinical Notes Series PredictionDongyu Zhang, Jidapa Thadajarassiri, Cansu Sen, Elke A. Rundensteiner. 566-588 [doi]
- Transfer Learning from Well-Curated to Less-Resourced Populations with HIVSonali Parbhoo, Mario Wieser, Volker Roth 0001, Finale Doshi-Velez. 589-609 [doi]
- Towards an Automated SOAP Note: Classifying Utterances from Medical ConversationsBenjamin Schloss, Sandeep Konam. 610-631 [doi]
- Query-Focused EHR Summarization to Aid Imaging DiagnosisDenis Jered McInerney, Borna Dabiri, Anne-Sophie Touret, Geoffrey Young, Jan-Willem van de Meent, Byron C. Wallace. 632-659 [doi]
- Predicting Drug Sensitivity of Cancer Cell Lines via Collaborative Filtering with Contextual AttentionYifeng Tao, Shuangxia Ren, Michael Q. Ding, Russell Schwartz, Xinghua Lu. 660-684 [doi]
- Using deep networks for scientific discovery in physiological signalsTom Beer, Bar Eini-Porat, Sebastian Goodfellow, Danny Eytan, Uri Shalit. 685-709 [doi]
- Hidden Risks of Machine Learning Applied to Healthcare: Unintended Feedback Loops Between Models and Future Data Causing Model DegradationGeorge-Alexandru Adam, Chun-Hao Kingsley Chang, Benjamin Haibe-Kains, Anna Goldenberg. 710-731 [doi]
- Self-Supervised Pretraining with DICOM metadata in Ultrasound ImagingSzu-Yeu Hu, Shuhang Wang, Wei-Hung Weng, Jingchao Wang, Xiaohong Wang, Arinc Ozturk, Quan Li, Viksit Kumar, Anthony E. Samir. 732-749 [doi]
- Deep Learning Applied to Chest X-Rays: Exploiting and Preventing ShortcutsSarah Jabbour, David Fouhey, Ella Kazerooni, Michael W. Sjoding, Jenna Wiens. 750-782 [doi]
- Clinical Collabsheets: 53 Questions to Guide a Clinical CollaborationShems Saleh, William Boag, Lauren Erdman, Tristan Naumann. 783-812 [doi]
- Non-Invasive Classification of Alzheimer's Disease Using Eye Tracking and LanguageOswald Barral, Hyeju Jang, Sally Newton-Mason, Sheetal Shajan, Thomas Soroski, Giuseppe Carenini, Cristina Conati, Thalia Shoshana Field. 813-841 [doi]
- Fast, Structured Clinical Documentation via Contextual AutocompleteDivya Gopinath, Monica Agrawal, Luke S. Murray, Steven Horng, David R. Karger, David A. Sontag. 842-870 [doi]
- Comparing Machine Learning Techniques for Blood Glucose Forecasting Using Free-living and Patient Generated DataHadia Hameed, Samantha Kleinberg. 871-894 [doi]
- UPSTAGE: Unsupervised Context Augmentation for Utterance Classification in Patient-Provider CommunicationDo June Min, Verónica Pérez-Rosas, Shihchen Kuo, William H. Herman, Rada Mihalcea. 895-912 [doi]
- CheXpert++: Approximating the CheXpert Labeler for Speed, Differentiability, and Probabilistic OutputMatthew B. A. McDermott, Tzu-Ming Harry Hsu, Wei-Hung Weng, Marzyeh Ghassemi, Peter Szolovits. 913-927 [doi]
- Robust Benchmarking for Machine Learning of Clinical Entity ExtractionMonica Agrawal, Chloe O'Connell, Yasmin Fatemi, Ariel Levy, David Sontag. 928-949 [doi]
- Preparing a Clinical Support Model for Silent Mode in General Internal MedicineBret Nestor, Liam G. McCoy, Amol Verma, Chloé Pou-Prom, Joshua Murray, Sebnem Kuzulugil, David Dai, Muhammad Mamdani, Anna Goldenberg, Marzyeh Ghassemi. 950-972 [doi]