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Proceedings of Machine Learning Research

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Proceedings of Machine Learning Research
PMLR · 2026-06-02 · via Proceedings of Machine Learning Research

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Volume 68: Machine Learning for Healthcare Conference, 18-19 August 2017, Boston, Massachusetts

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Editors: Finale Doshi-Velez, Jim Fackler, David Kale, Rajesh Ranganath, Byron Wallace, Jenna Wiens

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Piecewise-constant parametric approximations for survival learning

; Proceedings of the 2nd Machine Learning for Healthcare Conference, PMLR 68:1-12

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Spatially-Continuous Plantar Pressure Reconstruction Using Compressive Sensing

Amirreza Farnoosh, Sarah Ostadabbas, Mehrdad Nourani; Proceedings of the 2nd Machine Learning for Healthcare Conference, PMLR 68:13-24

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Classifying Lung Cancer Severity with Ensemble Machine Learning in Health Care Claims Data

Savannah L. Bergquist, Gabriel A. Brooks, Nancy L. Keating, Mary Beth Landrum, Sherri Rose; Proceedings of the 2nd Machine Learning for Healthcare Conference, PMLR 68:25-38

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Predicting long-term mortality with first week post-operative data after Coronary Artery Bypass Grafting using Machine Learning models

Jose Castela Forte, Marco A. Wiering, Hjalmar R. Bouma, Fred Geus, Anne H. Epema; Proceedings of the 2nd Machine Learning for Healthcare Conference, PMLR 68:39-58

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ShortFuse: Biomedical Time Series Representations in the Presence of Structured Information

Madalina Fiterau, Suvrat Bhooshan, Jason Fries, Charles Bournhonesque, Jennifer Hicks, Eni Halilaj, Christopher Re, Scott Delp; Proceedings of the 2nd Machine Learning for Healthcare Conference, PMLR 68:59-74

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Towards Vision-Based Smart Hospitals: A System for Tracking and Monitoring Hand Hygiene Compliance

Albert Haque, Michelle Guo, Alexandre Alahi, Serena Yeung, Zelun Luo, Alisha Rege, Jeffrey Jopling, Lance Downing, William Beninati, Amit Singh, Terry Platchek, Arnold Milstein, Li Fei-Fei; Proceedings of the 2nd Machine Learning for Healthcare Conference, PMLR 68:75-87

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Surgeon Technical Skill Assessment using Computer Vision based Analysis

Hei Law, Khurshid Ghani, Jia Deng; Proceedings of the 2nd Machine Learning for Healthcare Conference, PMLR 68:88-99

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Predicting Surgery Duration with Neural Heteroscedastic Regression

Nathan H Ng, Rodney A Gabriel, Julian McAuley, Charles Elkan, Zachary C Lipton; Proceedings of the 2nd Machine Learning for Healthcare Conference, PMLR 68(26):100-111

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Temporal prediction of multiple sclerosis evolution from patient-centered outcomes

Samuele Fiorini, Alessandro Verri, Annalisa Barla, Andrea Tacchino, Giampaolo Brichetto; Proceedings of the 2nd Machine Learning for Healthcare Conference, PMLR 68:112-125

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Clustering Patients with Tensor Decomposition

Matteo Ruffini, Ricard Gavalda, Esther Limon; Proceedings of the 2nd Machine Learning for Healthcare Conference, PMLR 68:126-146

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Continuous State-Space Models for Optimal Sepsis Treatment: a Deep Reinforcement Learning Approach

Aniruddh Raghu, Matthieu Komorowski, Leo Anthony Celi, Peter Szolovits, Marzyeh Ghassemi; Proceedings of the 2nd Machine Learning for Healthcare Conference, PMLR 68:147-163

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Modeling Progression Free Survival in Breast Cancer with Tensorized Recurrent Neural Networks and Accelerated Failure Time Models

Yinchong Yang, Peter A. Fasching, Volker Tresp; Proceedings of the 2nd Machine Learning for Healthcare Conference, PMLR 68:164-176

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Hawkes Process Modeling of Adverse Drug Reactions with Longitudinal Observational Data

Yujia Bao, Zhaobin Kuang, Peggy Peissig, David Page, Rebecca Willett; Proceedings of the 2nd Machine Learning for Healthcare Conference, PMLR 68:177-190

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Patient Similarity Using Population Statistics and Multiple Kernel Learning

Bryan Conroy, Minnan Xu-Wilson, Asif Rahman; Proceedings of the 2nd Machine Learning for Healthcare Conference, PMLR 68:191-203

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A Video-Based Method for Automatically Rating Ataxia

Ronnachai Jaroensri, Amy Zhao, Guha Balakrishnan, Derek Lo, Jeremy D. Schmahmann, Fredo Durand, John Guttag; Proceedings of the 2nd Machine Learning for Healthcare Conference, PMLR 68:204-216

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Visualizing Clinical Significance with Prediction and Tolerance Regions

Maria Jahja, Daniel J. Lizotte; Proceedings of the 2nd Machine Learning for Healthcare Conference, PMLR 68:217-230

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Predictive Hierarchical Clustering: Learning clusters of CPT codes for improving surgical outcomes

Elizabeth C. Lorenzi, Stephanie L. Brown, Zhifei Sun, Katherine Heller; Proceedings of the 2nd Machine Learning for Healthcare Conference, PMLR 68:231-242

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An Improved Multi-Output Gaussian Process RNN with Real-Time Validation for Early Sepsis Detection

Joseph Futoma, Sanjay Hariharan, Katherine Heller, Mark Sendak, Nathan Brajer, Meredith Clement, Armando Bedoya, Cara O’Brien; Proceedings of the 2nd Machine Learning for Healthcare Conference, PMLR 68:243-254

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Marked Point Process for Severity of Illness Assessment

Kazi T. Islam, Christian R. Shelton, Juan I. Casse, Randall Wetzel; Proceedings of the 2nd Machine Learning for Healthcare Conference, PMLR 68:255-270

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Diagnostic Inferencing via Improving Clinical Concept Extraction with Deep Reinforcement Learning: A Preliminary Study

Yuan Ling, Sadid A. Hasan, Vivek Datla, Ashequl Qadir, Kathy Lee, Joey Liu, Oladimeji Farri; Proceedings of the 2nd Machine Learning for Healthcare Conference, PMLR 68:271-285

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Generating Multi-label Discrete Patient Records using Generative Adversarial Networks

Edward Choi, Siddharth Biswal, Bradley Malin, Jon Duke, Walter F. Stewart, Jimeng Sun; Proceedings of the 2nd Machine Learning for Healthcare Conference, PMLR 68:286-305

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Quantifying Mental Health from Social Media with Neural User Embeddings

Silvio Amir, Glen Coppersmith, Paula Carvalho, Mario J. Silva, Bryon C. Wallace; Proceedings of the 2nd Machine Learning for Healthcare Conference, PMLR 68:306-321

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Clinical Intervention Prediction and Understanding with Deep Neural Networks

Harini Suresh, Nathan Hunt, Alistair Johnson, Leo Anthony Celi, Peter Szolovits, Marzyeh Ghassemi; Proceedings of the 2nd Machine Learning for Healthcare Conference, PMLR 68:322-337

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Understanding Coagulopathy using Multi-view Data in the Presence of Sub-Cohorts: A Hierarchical Subspace Approach

Arya A. Pourzanjani, Tie Bo Wu, Richard M. Jiang, Mitchell J. Cohen, Linda R. Petzold; Proceedings of the 2nd Machine Learning for Healthcare Conference, PMLR 68:338-351

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Towards a Directory of Rare Disease Specialists: Identifying Experts from Publication History

Zihan Wang, Michael Brudno, Orion Buske; Proceedings of the 2nd Machine Learning for Healthcare Conference, PMLR 68:352-360

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Reproducibility in critical care: a mortality prediction case study

Alistair E. W. Johnson, Tom J. Pollard, Roger G. Mark; Proceedings of the 2nd Machine Learning for Healthcare Conference, PMLR 68:361-376

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