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MLHC 2019: Ann Arbor, Michigan, USA
- Finale Doshi-Velez, Jim Fackler, Ken Jung, David C. Kale, Rajesh Ranganath, Byron C. Wallace, Jenna Wiens: 
 Proceedings of the Machine Learning for Healthcare Conference, MLHC 2019, 9-10 August 2019, Ann Arbor, Michigan, USA. Proceedings of Machine Learning Research 106, PMLR 2019
- Michael Moor, Max Horn  , Bastian Rieck , Bastian Rieck , Damian Roqueiro, Karsten M. Borgwardt: , Damian Roqueiro, Karsten M. Borgwardt:
 Early Recognition of Sepsis with Gaussian Process Temporal Convolutional Networks and Dynamic Time Warping. 2-26
- Jeeheh Oh  , Jiaxuan Wang, Shengpu Tang , Jiaxuan Wang, Shengpu Tang , Michael W. Sjoding, Jenna Wiens: , Michael W. Sjoding, Jenna Wiens:
 Relaxed Parameter Sharing: Effectively Modeling Time-Varying Relationships in Clinical Time-Series. 27-52
- Surya Teja Devarakonda, Yeahuay Joie Wu, Yi Ren Fung, Madalina Fiterau: 
 FLARe: Forecasting by Learning Anticipated Representations. 53-65
- Iñigo Urteaga, Tristan Bertin, Theresa M. Hardy, David J. Albers, Noémie Elhadad: 
 Multi-Task Gaussian Processes and Dilated Convolutional Networks for Reconstruction of Reproductive Hormonal Dynamics. 66-90
- Mohammad Akbari, Rumi Chunara: 
 Using Contextual Information to Improve Blood Glucose Prediction. 91-108
- Chirag Nagpal, Xinyu Li, Michael R. Pinsky, Artur Dubrawski: 
 Dynamically Personalized Detection of Hemorrhage. 109-123
- Divya Shanmugam, Davis W. Blalock, John V. Guttag: 
 Multiple Instance Learning for ECG Risk Stratification. 124-139
- Supriya Nagesh, Alexander Moreno, Hiroshi Ishikawa, Gadi Wollstein, Joel S. Schuman, James M. Rehg: 
 A Spatiotemporal Approach to Predicting Glaucoma Progression Using a CT-HMM. 140-159
- Ian C. Covert, Balu Krishnan, Imad Najm, Jiening Zhan, Matthew Shore, John Hixson, Ming Jack Po: 
 Temporal Graph Convolutional Networks for Automatic Seizure Detection. 160-180
- Ognjen (Oggi) Rudovic, Yuria Utsumi, Ricardo Guerrero, Kelly Peterson, Daniel Rueckert, Rosalind W. Picard: 
 Meta-Weighted Gaussian Process Experts for Personalized Forecasting of AD Cognitive Changes. 181-196
- Keyang Xu, Mike Lam, Jingzhi Pang, Xin Gao, Charlotte Band, Piyush Mathur, Frank Papay, Ashish K. Khanna, Jacek B. Cywinski, Kamal Maheshwari, Pengtao Xie, Eric P. Xing: 
 Multimodal Machine Learning for Automated ICD Coding. 197-215
- Bhanu Pratap Singh Rawat, Fei Li, Hong Yu: 
 Clinical Judgement Study using Question Answering from Electronic Health Records. 216-229
- Bonggun Shin, Sungsoo Park, Keunsoo Kang, Joyce C. Ho: 
 Self-Attention Based Molecule Representation for Predicting Drug-Target Interaction. 230-248
- Guanxiong Liu, Tzu-Ming Harry Hsu, Matthew B. A. McDermott, Willie Boag, Wei-Hung Weng, Peter Szolovits, Marzyeh Ghassemi: 
 Clinically Accurate Chest X-Ray Report Generation. 249-269
- Weirui Kong, Hyeju Jang, Giuseppe Carenini, Thalia Shoshana Field  : :
 A Neural Model for Predicting Dementia from Language. 270-286
- Grace Guan, Barbara E. Engelhardt: 
 Predicting Sick Patient Volume in a Pediatric Outpatient Setting using Time Series Analysis. 271-287
- Youran Qi, Qi Tang: 
 Predicting Phase 3 Clinical Trial Results by Modeling Phase 2 Clinical Trial Subject Level Data Using Deep Learning. 288-303
- Victor Alfonso Rodriguez, Adler J. Perotte: 
 Phenotype Inference with Semi-Supervised Mixed Membership Models. 304-324
- Stephen R. Pfohl, Tony Duan, Daisy Yi Ding, Nigam H. Shah: 
 Counterfactual Reasoning for Fair Clinical Risk Prediction. 325-358
- Sana Tonekaboni, Shalmali Joshi, Melissa D. McCradden, Anna Goldenberg: 
 What Clinicians Want: Contextualizing Explainable Machine Learning for Clinical End Use. 359-380
- Bret Nestor, Matthew B. A. McDermott, Willie Boag, Gabriela Berner, Tristan Naumann, Michael C. Hughes  , Anna Goldenberg, Marzyeh Ghassemi: , Anna Goldenberg, Marzyeh Ghassemi:
 Feature Robustness in Non-stationary Health Records: Caveats to Deployable Model Performance in Common Clinical Machine Learning Tasks. 381-405
- Avijit Thawani, Michael J. Paul, Urmimala Sarkar, Byron C. Wallace: 
 Are Online Reviews of Physicians Biased Against Female Providers? 406-423
- Steve Yadlowsky, Sanjay Basu, Lu Tian: 
 A Calibration Metric for Risk Scores with Survival Data. 424-450
- Jinsung Yoon, James Jordon, Mihaela van der Schaar: 
 ASAC: Active Sensing using Actor-Critic models. 451-473
- Min Zheng, Samantha Kleinberg: 
 Using Domain Knowledge to Overcome Latent Variables in Causal Inference from Time Series. 474-489
- Linying Zhang, Yixin Wang, Anna Ostropolets, Jami J. Mulgrave, David M. Blei, George Hripcsak: 
 The Medical Deconfounder: Assessing Treatment Effects with Electronic Health Records. 490-512
- Siddharth Biswal, Cao Xiao, M. Brandon Westover, Jimeng Sun: 
 EEGtoText: Learning to Write Medical Reports from EEG Recordings. 513-531
- Viraj Prabhu, Anitha Kannan, Murali Ravuri, Manish Chaplain, David A. Sontag, Xavier Amatriain: 
 Few-Shot Learning for Dermatological Disease Diagnosis. 532-552
- David Dov, Shahar Z. Kovalsky, Jonathan Cohen, Danielle Elliott Range, Ricardo Henao, Lawrence Carin: 
 Thyroid Cancer Malignancy Prediction From Whole Slide Cytopathology Images. 553-570
- Trent Kyono, Fiona J. Gilbert, Mihaela van der Schaar: 
 Multi-view Multi-task Learning for Improving Autonomous Mammogram Diagnosis. 571-591
- Hao-Chih Lee, Sarah T. Cherng, Riccardo Miotto, Joel T. Dudley: 
 Enhancing high-content imaging for studying microtubule networks at large-scale. 592-613
- Charles Hamesse, Ruibo Tu, Paul Ackermann, Hedvig Kjellström, Cheng Zhang: 
 Simultaneous Measurement Imputation and Outcome Prediction for Achilles Tendon Rupture Rehabilitation. 614-640
- Mark Mirtchouk, Dana L. McGuire, Andrea L. Deierlein, Samantha Kleinberg: 
 Automated Estimation of Food Type from Body-worn Audio and Motion Sensors in Free-Living Environments. 641-662
- Tingfung Lau, Nathan Ng, Julian Gingold, Nina Desai, Julian J. McAuley, Zachary C. Lipton: 
 Embryo Staging with Weakly-Supervised Region Selection and Dynamically-Decoded Predictions. 663-679
- Shiva Kaul, Anthony Falco, Karianne Anthes: 
 Measuring the Sympathetic Response to Intense Exercise in a Practical Setting. 680-703
- Jose Javier Gonzalez Ortiz, Daryush D. Mehta, Jarrad H. Van Stan, Robert E. Hillman, John V. Guttag, Marzyeh Ghassemi: 
 Learning from Few Subjects with Large Amounts of Voice Monitoring Data. 704-720
- Irfan Al-Hussaini, Cao Xiao, M. Brandon Westover, Jimeng Sun: 
 SLEEPER: interpretable Sleep staging via Prototypes from Expert Rules. i

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