Early Recognition of Sepsis with Gaussian Process Temporal Convolutional Networks and Dynamic Time Warping

Michael Moor, Max Horn, Bastian Rieck, Damian Roqueiro, Karsten Borgwardt; 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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