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Proceedings of Machine Learning Research

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

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Volume 136: Machine Learning for Health, 11 December 2020, Virtual

[edit]

Editors: Emily Alsentzer, Matthew B. A. McDermott, Fabian Falck, Suproteem K. Sarkar, Subhrajit Roy, Stephanie L. Hyland

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Machine Learning for Health (ML4H) 2020: Advancing Healthcare for All

Suproteem K. Sarkar, Subhrajit Roy, Emily Alsentzer, Matthew B. A. McDermott, Fabian Falck, Ioana Bica, Griffin Adams, Stephen Pfohl, Stephanie L. Hyland; Proceedings of the Machine Learning for Health NeurIPS Workshop, PMLR 136:1-11

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Zero-Shot Clinical Acronym Expansion via Latent Meaning Cells

; Proceedings of the Machine Learning for Health NeurIPS Workshop, PMLR 136:12-40

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Quantifying Common Support between Multiple Treatment Groups Using a Contrastive-VAE

Wangzhi Dai, Collin M. Stultz; Proceedings of the Machine Learning for Health NeurIPS Workshop, PMLR 136:41-52

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A Bayesian Hierarchical Network for Combining Heterogeneous Data Sources in Medical Diagnoses

Claire Donnat, Nina Miolane, Freddy Bunbury, Jack Kreindler; Proceedings of the Machine Learning for Health NeurIPS Workshop, PMLR 136:53-84

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Neural Temporal Point Processes For Modelling Electronic Health Records

Joseph Enguehard, Dan Busbridge, Adam Bozson, Claire Woodcock, Nils Hammerla; Proceedings of the Machine Learning for Health NeurIPS Workshop, PMLR 136:85-113

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Parkinsonian Chinese Speech Analysis towards Automatic Classification of Parkinson's Disease

Hao Fang, Chen Gong, Chen Zhang, Yanan Sui, Luming Li; Proceedings of the Machine Learning for Health NeurIPS Workshop, PMLR 136:114-125

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sEMG Gesture Recognition with a Simple Model of Attention

David Josephs, Carson Drake, Andy Heroy, John Santerre; Proceedings of the Machine Learning for Health NeurIPS Workshop, PMLR 136:126-138

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An Empirical Study of Representation Learning for Reinforcement Learning in Healthcare

Taylor W. Killian, Haoran Zhang, Jayakumar Subramanian, Mehdi Fatemi, Marzyeh Ghassemi; Proceedings of the Machine Learning for Health NeurIPS Workshop, PMLR 136:139-160

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Improved Clinical Abbreviation Expansion via Non-Sense-Based Approaches

Juyong Kim, Linyuan Gong, Justin Khim, Jeremy C. Weiss, Pradeep Ravikumar; Proceedings of the Machine Learning for Health NeurIPS Workshop, PMLR 136:161-178

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Appropriate Evaluation of Diagnostic Utility of Machine Learning Algorithm Generated Images

Young Joon Kwon, Danielle Toussie, Lea Azour, Jose Concepcion, Corey Eber, G. Anthony Reina, Ping Tak Peter Tang, Amish H. Doshi, Eric K. Oermann, Anthony B. Costa; Proceedings of the Machine Learning for Health NeurIPS Workshop, PMLR 136:179-193

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DeepHeartBeat: Latent trajectory learning of cardiac cycles using cardiac ultrasounds

Fabian Laumer, Gabriel Fringeli, Alina Dubatovka, Laura Manduchi, Joachim M. Buhmann; Proceedings of the Machine Learning for Health NeurIPS Workshop, PMLR 136:194-212

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Spectral discontinuity design: Interrupted time series with spectral mixture kernels

David Leeftink, Max Hinne; Proceedings of the Machine Learning for Health NeurIPS Workshop, PMLR 136:213-225

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3D Photography Based Neural Network Craniosynostosis Triaging System

Pouria Mashouri, Marta Skreta, John Phillips, Dianna McAllister, Melissa Roy, Senthujan Senkaiahliyan, Michael Brudno, Devin Singh; Proceedings of the Machine Learning for Health NeurIPS Workshop, PMLR 136:226-237

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Contrastive Representation Learning for Electroencephalogram Classification

Mostafa Neo Mohsenvand, Mohammad Rasool Izadi, Pattie Maes; Proceedings of the Machine Learning for Health NeurIPS Workshop, PMLR 136:238-253

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A Neural SIR Model for Global Forecasting

Philip Nadler, Rossella Arcucci, Yike Guo; Proceedings of the Machine Learning for Health NeurIPS Workshop, PMLR 136:254-266

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Attend and Decode: 4D fMRI Task State Decoding Using Attention Models

Sam Nguyen, Brenda Ng, Alan D. Kaplan, Priyadip Ray; Proceedings of the Machine Learning for Health NeurIPS Workshop, PMLR 136:267-279

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ML4H Auditing: From Paper to Practice

Luis Oala, Jana Fehr, Luca Gilli, Pradeep Balachandran, Alixandro Werneck Leite, Saul Calderon-Ramirez, Danny Xie Li, Gabriel Nobis, Erick Alejandro Muñoz Alvarado, Giovanna Jaramillo-Gutierrez, Christian Matek, Arun Shroff, Ferath Kherif, Bruno Sanguinetti, Thomas Wiegand; Proceedings of the Machine Learning for Health NeurIPS Workshop, PMLR 136:280-317

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CheXphoto: 10,000+ Photos and Transformations of Chest X-rays for Benchmarking Deep Learning Robustness

Nick A. Phillips, Pranav Rajpurkar, Mark Sabini, Rayan Krishnan, Sharon Zhou, Anuj Pareek, Nguyet Minh Phu, Chris Wang, Mudit Jain, Nguyen Duong Du, Steven QH Truong, Andrew Y. Ng, Matthew P. Lungren; Proceedings of the Machine Learning for Health NeurIPS Workshop, PMLR 136:318-327

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Evaluation of Contrastive Predictive Coding for Histopathology Applications

Karin Stacke, Claes Lundström, Jonas Unger, Gabriel Eilertsen; Proceedings of the Machine Learning for Health NeurIPS Workshop, PMLR 136:328-340

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Trust Issues: Uncertainty Estimation Does Not Enable Reliable OOD Detection On Medical Tabular Data

Dennis Ulmer, Lotta Meijerink, Giovanni Cinà; Proceedings of the Machine Learning for Health NeurIPS Workshop, PMLR 136:341-354

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Interpretable Epilepsy Detection in Routine, Interictal EEG Data using Deep Learning

Thomas Uyttenhove, Aren Maes, Tom Van Steenkiste, Dirk Deschrijver, Tom Dhaene; Proceedings of the Machine Learning for Health NeurIPS Workshop, PMLR 136:355-366

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EEG-GCNN: Augmenting Electroencephalogram-based Neurological Disease Diagnosis using a Domain-guided Graph Convolutional Neural Network

Neeraj Wagh, Yogatheesan Varatharajah; Proceedings of the Machine Learning for Health NeurIPS Workshop, PMLR 136:367-378

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Confounding Feature Acquisition for Causal Effect Estimation

Shirly Wang, Seung Eun Yi, Shalmali Joshi, Marzyeh Ghassemi; Proceedings of the Machine Learning for Health NeurIPS Workshop, PMLR 136:379-396

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TL-Lite: Temporal Visualization and Learning for Clinical Forecasting

Jeremy C. Weiss; Proceedings of the Machine Learning for Health NeurIPS Workshop, PMLR 136:397-414

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Addressing the Real-world Class Imbalance Problem in Dermatology

Wei-Hung Weng, Jonathan Deaton, Vivek Natarajan, Gamaleldin F. Elsayed, Yuan Liu; Proceedings of the Machine Learning for Health NeurIPS Workshop, PMLR 136:415-429

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此内容由惯性聚合(RSS阅读器)自动聚合整理，仅供阅读参考。 原文来自 — 版权归原作者所有。