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Editors: Finale Doshi-Velez, Jim Fackler, Ken Jung, David Kale, Rajesh Ranganath, Byron Wallace, Jenna Wiens
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Early Recognition of Sepsis with Gaussian Process Temporal Convolutional Networks and Dynamic Time Warping
; Proceedings of the 4th Machine Learning for Healthcare Conference, PMLR 106:2-26
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Relaxed Parameter Sharing: Effectively Modeling Time-Varying Relationships in Clinical Time-Series
Jeeheh Oh, Jiaxuan Wang, Shengpu Tang, Michael W. Sjoding, Jenna Wiens; Proceedings of the 4th Machine Learning for Healthcare Conference, PMLR 106:27-52
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FLARe: Forecasting by Learning Anticipated Representations
Surya Teja Devarakonda, Joie Yeahuay Wu, Yi Ren Fung, Madalina Fiterau; Proceedings of the 4th Machine Learning for Healthcare Conference, PMLR 106:53-65
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Multi-Task Gaussian Processes and Dilated Convolutional Networks for Reconstruction of Reproductive Hormonal Dynamics
Iñigo Urteaga, Tristan Bertin, Theresa M. Hardy, David J. Albers, Noémie Elhadad; Proceedings of the 4th Machine Learning for Healthcare Conference, PMLR 106:66-90
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Using Contextual Information to Improve Blood Glucose Prediction
Mohammad Akbari, Rumi Chunara; Proceedings of the 4th Machine Learning for Healthcare Conference, PMLR 106:91-108
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Dynamically Personalized Detection of Hemorrhage
Chirag Nagpal, Xinyu Li, Michael R. Pinsky, Artur Dubrawski; Proceedings of the 4th Machine Learning for Healthcare Conference, PMLR 106:109-123
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Multiple Instance Learning for ECG Risk Stratification
Divya Shanmugam, Davis Blalock, John Guttag; Proceedings of the 4th Machine Learning for Healthcare Conference, PMLR 106:124-139
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A Spatiotemporal Approach to Predicting Glaucoma Progression Using a CT-HMM
Supriya Nagesh, Alexander Moreno, Hiroshi Ishikawa, Gadi Wollstein, Joel S. Shuman, James M. Rehg; Proceedings of the 4th Machine Learning for Healthcare Conference, PMLR 106:140-159
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Temporal Graph Convolutional Networks for Automatic Seizure Detection
Ian C. Covert, Balu Krishnan, Imad Najm, Jiening Zhan, Matthew Shore, John Hixson, Ming Jack Po; Proceedings of the 4th Machine Learning for Healthcare Conference, PMLR 106:160-180
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Meta-Weighted Gaussian Process Experts for Personalized Forecasting of AD Cognitive Changes
Ognjen (Oggi) Rudovic, Yuria Utsumi, Ricardo Guerrero, Kelly Peterson, Daniel Rueckert, Rosalind W. Picard; Proceedings of the 4th Machine Learning for Healthcare Conference, PMLR 106:181-196
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Multimodal Machine Learning for Automated ICD Coding
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; Proceedings of the 4th Machine Learning for Healthcare Conference, PMLR 106:197-215
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Clinical Judgement Study using Question Answering from Electronic Health Records
Bhanu Pratap Singh Rawat, Fe Li, Hong Yu; Proceedings of the 4th Machine Learning for Healthcare Conference, PMLR 106:216-229
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Self-Attention Based Molecule Representation for Predicting Drug-Target Interaction
Bonggun Shin, Sungsoo Park, Keunsoo Kang, Joyce C. Ho; Proceedings of the 4th Machine Learning for Healthcare Conference, PMLR 106:230-248
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Clinically Accurate Chest X-Ray Report Generation
Guanxiong Liu, Tzu-Ming Harry Hsu, Matthew McDermott, Willie Boag, Wei-Hung Weng, Peter Szolovits, Marzyeh Ghassemi; Proceedings of the 4th Machine Learning for Healthcare Conference, PMLR 106:249-269
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A Neural Model for Predicting Dementia from Language
Weirui Kong, Hyeju Jang, Giuseppe Carenini, Thalia Field; Proceedings of the 4th Machine Learning for Healthcare Conference, PMLR 106:270-286
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Predicting Sick Patient Volume in a Pediatric Outpatient Setting using Time Series Analysis
Grace Guan, Barbara E. Engelhardt; Proceedings of the 4th Machine Learning for Healthcare Conference, PMLR 106:271-287
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Predicting Phase 3 Clinical Trial Results by Modeling Phase 2 Clinical Trial Subject Level Data Using Deep Learning
Youran Qi, Qi Tang; Proceedings of the 4th Machine Learning for Healthcare Conference, PMLR 106:288-303
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Phenotype Inference with Semi-Supervised Mixed Membership Models
Victor A. Rodriguez, Adler Perotte; Proceedings of the 4th Machine Learning for Healthcare Conference, PMLR 106:304-324
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Counterfactual Reasoning for Fair Clinical Risk Prediction
Stephen R. Pfohl, Tony Duan, Daisy Yi Ding, Nigam H. Shah; Proceedings of the 4th Machine Learning for Healthcare Conference, PMLR 106:325-358
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What Clinicians Want: Contextualizing Explainable Machine Learning for Clinical End Use
Sana Tonekaboni, Shalmali Joshi, Melissa D. McCradden, Anna Goldenberg; Proceedings of the 4th Machine Learning for Healthcare Conference, PMLR 106:359-380
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Feature Robustness in Non-stationary Health Records: Caveats to Deployable Model Performance in Common Clinical Machine Learning Tasks
Bret Nestor, Matthew B. A. McDermott, Willie Boag, Gabriela Berner, Tristan Naumann, Michael C. Hughes, Anna Goldenberg, Marzyeh Ghassemi; Proceedings of the 4th Machine Learning for Healthcare Conference, PMLR 106:381-405
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Are Online Reviews of Physicians Biased Against Female Providers?
Avijit Thawani, Michael J. Paul, Urmimala Sarkar, Byron C. Wallace; Proceedings of the 4th Machine Learning for Healthcare Conference, PMLR 106:406-423
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A Calibration Metric for Risk Scores with Survival Data
Steve Yadlowsky, Sanjay Basu, Lu Tian; Proceedings of the 4th Machine Learning for Healthcare Conference, PMLR 106:424-450
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ASAC: Active Sensing using Actor-Critic models
Jinsung Yoon, James Jordon, Mihaela Schaar; Proceedings of the 4th Machine Learning for Healthcare Conference, PMLR 106:451-473
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Using Domain Knowledge to Overcome Latent Variables in Causal Inference from Time Series
Min Zheng, Samantha Kleinberg; Proceedings of the 4th Machine Learning for Healthcare Conference, PMLR 106:474-489
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The Medical Deconfounder: Assessing Treatment Effects with Electronic Health Records
Linying Zhang, Yixin Wang, Anna Ostropolets, Jami J. Mulgrave, David M. Blei, George Hripcsak; Proceedings of the 4th Machine Learning for Healthcare Conference, PMLR 106:490-512
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EEGtoText: Learning to Write Medical Reports from EEG Recordings
Siddharth Biswal, Cao Xiao, M. Brandon Westover, Jimeng Sun; Proceedings of the 4th Machine Learning for Healthcare Conference, PMLR 106:513-531
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Few-Shot Learning for Dermatological Disease Diagnosis
Viraj Prabhu, Anitha Kannan, Murali Ravuri, Manish Chaplain, David Sontag, Xavier Amatriain; Proceedings of the 4th Machine Learning for Healthcare Conference, PMLR 106:532-552
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Thyroid Cancer Malignancy Prediction From Whole Slide Cytopathology Images
David Dov, Shahar Z. Kovalsky, Jonathan Cohen, Danielle Elliott Range, Ricardo Henao, Lawrence Carin; Proceedings of the 4th Machine Learning for Healthcare Conference, PMLR 106:553-570
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Multi-view Multi-task Learning for Improving Autonomous Mammogram Diagnosis
Trent Kyono, Fiona J. Gilbert, Mihaela Schaar; Proceedings of the 4th Machine Learning for Healthcare Conference, PMLR 106:571-591
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Enhancing high-content imaging for studying microtubule networks at large-scale
Hao-Chih Lee, Sarah T. Cherng, Riccardo Miotto, Joel T. Dudley; Proceedings of the 4th Machine Learning for Healthcare Conference, PMLR 106:592-613
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Simultaneous Measurement Imputation and Outcome Prediction for Achilles Tendon Rupture Rehabilitation
Charles Hamesse, Ruibo Tu, Paul Ackermann, Hedvig Kjellström, Cheng Zhang; Proceedings of the 4th Machine Learning for Healthcare Conference, PMLR 106:614-640
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Automated Estimation of Food Type from Body-worn Audio and Motion Sensors in Free-Living Environments
Mark Mirtchouk, Dana L. McGuire, Andrea L. Deierlein, Samantha Kleinberg; Proceedings of the 4th Machine Learning for Healthcare Conference, PMLR 106:641-662
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Embryo Staging with Weakly-Supervised Region Selection and Dynamically-Decoded Predictions
Tingfung Lau, Nathan Ng, Julian Gingold, Nina Desai, Julian McAuley, Zachary C. Lipton; Proceedings of the 4th Machine Learning for Healthcare Conference, PMLR 106:663-679
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Measuring the Sympathetic Response to Intense Exercise in a Practical Setting
Shiva Kaul, Anthony Falco, Karianne Anthes; Proceedings of the 4th Machine Learning for Healthcare Conference, PMLR 106:680-703
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Learning from Few Subjects with Large Amounts of Voice Monitoring Data
Jose Javier Gonzalez Ortiz, Daryush D. Mehta, Jarrad H. Van Stan, Robert Hillman, John V. Guttag, Marzeyeh Ghassemi; Proceedings of the 4th Machine Learning for Healthcare Conference, PMLR 106:704-720
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SLEEPER: interpretable Sleep staging via Prototypes from Expert Rules
Irfan Al-Hussaini, Cao Xiao, M. Brandon Westover, Jimeng Sun; Proceedings of the 4th Machine Learning for Healthcare Conference, PMLR 106:721-739
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