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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 219: Machine Learning for Healthcare Conference, 11-12 August 2023, New York, USA

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Editors: Kaivalya Deshpande, Madalina Fiterau, Shalmali Joshi, Zachary Lipton, Rajesh Ranganath, Iñigo Urteaga, Serene Yeung

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A Meta-Evaluation of Faithfulness Metrics for Long-Form Hospital-Course Summarization

; Proceedings of the 8th Machine Learning for Healthcare Conference, PMLR 219:2-30

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Which Explanation Makes Sense? A Critical Evaluation of Local Explanations for Assessing Cervical Cancer Risk

Celia Wafa Ayad, Thomas Bonnier, Benjamin Bosch, Jesse Read, Sonali Parbhoo; Proceedings of the 8th Machine Learning for Healthcare Conference, PMLR 219:31-49

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Anomaly Detection in Human Brain via Inductive Learning on Temporal Multiplex Networks

Ali Behrouz, Margo Seltzer; Proceedings of the 8th Machine Learning for Healthcare Conference, PMLR 219:50-75

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EEG to fMRI Synthesis Benefits from Attentional Graphs of Electrode Relationships

David Calhas, Rui Henriques; Proceedings of the 8th Machine Learning for Healthcare Conference, PMLR 219:76-93

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Typed Markers and Context for Clinical Temporal Relation Extraction

Cheng Cheng, Jeremy C. Weiss; Proceedings of the 8th Machine Learning for Healthcare Conference, PMLR 219:94-109

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When More is Less: Incorporating Additional Datasets Can Hurt Performance By Introducing Spurious Correlations

Rhys Compton, Lily Zhang, Aahlad Puli, Rajesh Ranganath; Proceedings of the 8th Machine Learning for Healthcare Conference, PMLR 219:110-127

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Fair Survival Time Prediction via Mutual Information Minimization

Hyungrok Do, Yuxin Chang, Yoon Sang Cho, Padhraic Smyth, Judy Zhong; Proceedings of the 8th Machine Learning for Healthcare Conference, PMLR 219:128-149

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Privacy-preserving patient clustering for personalized federated learnings

Ahmed Elhussein, Gamze Gürsoy; Proceedings of the 8th Machine Learning for Healthcare Conference, PMLR 219:150-166

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Bringing At-home Pediatric Sleep Apnea Testing Closer to Reality: A Multi-modal Transformer Approach

Hamed Fayyaz, Abigail Strang, Rahmatollah Beheshti; Proceedings of the 8th Machine Learning for Healthcare Conference, PMLR 219:167-185

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CDANs: Temporal Causal Discovery from Autocorrelated and Non-Stationary Time Series Data

Muhammad Hasan Ferdous, Uzma Hasan, Md Osman Gani; Proceedings of the 8th Machine Learning for Healthcare Conference, PMLR 219:186-207

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Composition Counts: A Machine Learning View on Immunothrombosis using Quantitative Phase Imaging

David Fresacher, Stefan Röhrl, Christian Klenk, Johanna Erber, Hedwig Irl, Dominik Heim, Manuel Lengl, Simon Schumann, Martin Knopp, Martin Schlegel, Sebastian Rasch, Oliver Hayden, Klaus Diepold; Proceedings of the 8th Machine Learning for Healthcare Conference, PMLR 219:208-229

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Online Unsupervised Representation Learning of Waveforms in the Intensive Care Unit via a novel cooperative framework: Spatially Resolved Temporal Networks (SpaRTEn)

Faris Gulamali, Ashwin Sawant, Ira Hofer, Matthew Levin, Alexander Charney, Karandeep Singh, Benjamin Glicksberg, Girish Nadkarni; Proceedings of the 8th Machine Learning for Healthcare Conference, PMLR 219:230-247

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Contactless Oxygen Monitoring with Radio Waves and Gated Transformer

Hao He, Yuan Yuan, Ying-Cong Chen, Peng Cao, Dina Katabi; Proceedings of the 8th Machine Learning for Healthcare Conference, PMLR 219:248-265

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Multi-view Modelling of Longitudinal Health Data for Improved Prognostication of Colorectal Cancer Recurrence

Danliang Ho, Mehul Motani; Proceedings of the 8th Machine Learning for Healthcare Conference, PMLR 219:265-284

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Detecting Heart Disease from Multi-View Ultrasound Images via Supervised Attention Multiple Instance Learning

Zhe Huang, Benjamin S. Wessler, Michael C. Hughes; Proceedings of the 8th Machine Learning for Healthcare Conference, PMLR 219:285-307

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Hawkes Process with Flexible Triggering Kernels

Yamac Isik, Paidamoyo Chapfuwa, Connor Davis, Ricardo Henao; Proceedings of the 8th Machine Learning for Healthcare Conference, PMLR 219:308-320

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Deep Metric Learning for the Hemodynamics Inference with Electrocardiogram Signals

Hyewon Jeong, Collin M. Stultz, Marzyeh Ghassemi; Proceedings of the 8th Machine Learning for Healthcare Conference, PMLR 219:321-342

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Conceptualizing Machine Learning for Dynamic Information Retrieval of Electronic Health Record Notes

Sharon Jiang, Shannon Shen, Monica Agrawal, Barbara Lam, Nicholas Kurtzman, Steven Horng, David R. Karger, David Sontag; Proceedings of the 8th Machine Learning for Healthcare Conference, PMLR 219:343-359

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Maximum Likelihood Estimation of Flexible Survival Densities with Importance Sampling

Mert Ketenci, Shreyas Bhave, Noemie Elhadad, Adler Perotte; Proceedings of the 8th Machine Learning for Healthcare Conference, PMLR 219:360-380

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RadGraph2: Modeling Disease Progression in Radiology Reports via Hierarchical Information Extraction

Sameer Khanna, Adam Dejl, Kibo Yoon, Steven QH Truong, Hanh Duong, Agustina Saenz, Pranav Rajpurkar; Proceedings of the 8th Machine Learning for Healthcare Conference, PMLR 219:381-402

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DuETT: Dual Event Time Transformer for Electronic Health Records

Alex Labach, Aslesha Pokhrel, Xiao Shi Huang, Saba Zuberi, Seung Eun Yi, Maksims Volkovs, Tomi Poutanen, Rahul G. Krishnan; Proceedings of the 8th Machine Learning for Healthcare Conference, PMLR 219:403-422

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Learning Missing Modal Electronic Health Records with Unified Multi-modal Data Embedding and Modality-Aware Attention

Kwanhyung Lee, Soojeong Lee, Sangchul Hahn, Heejung Hyun, Edward Choi, Byungeun Ahn, Joohyung Lee; Proceedings of the 8th Machine Learning for Healthcare Conference, PMLR 219:423-442

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Coarse race data conceals disparities in clinical risk score performance

Rajiv Movva, Divya Shanmugam, Kaihua Hou, Priya Pathak, John Guttag, Nikhil Garg, Emma Pierson; Proceedings of the 8th Machine Learning for Healthcare Conference, PMLR 219:443-472

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Reducing Contextual Bias in Cardiac Magnetic Resonance Imaging Deep Learning Using Contrastive Self-Supervision

Makiya Nakashima, Donna Salem, HW Wilson Tang, Christopher Nguyen, Tae Hyun Hwang, Ding Zhao, Byung-Hak Kim, Deborah Kwon, David Chen; Proceedings of the 8th Machine Learning for Healthcare Conference, PMLR 219:473-488

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ScoEHR: Generating Synthetic Electronic Health Records using Continuous-time Diffusion Models

Ahmed Ammar Naseer, Benjamin Walker, Christopher Landon, Andrew Ambrosy, Marat Fudim, Nicholas Wysham, Botros Toro, Sumanth Swaminathan, Terry Lyons; Proceedings of the 8th Machine Learning for Healthcare Conference, PMLR 219:489-508

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PrivECG: generating private ECG for end-to-end anonymization

Alexis Nolin-Lapalme, Robert Avram, Hussin Julie; Proceedings of the 8th Machine Learning for Healthcare Conference, PMLR 219:509-528

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Updating Clinical Risk Stratification Models Using Rank-Based Compatibility: Approaches for Evaluating and Optimizing Clinician-Model Team Performance

Erkin Ötles, Brian T. Denton, Jenna Wiens; Proceedings of the 8th Machine Learning for Healthcare Conference, PMLR 219:529-547

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TIER: Text-Image Entropy Regularization for Medical CLIP-style models

Anil Palepu, Andrew Beam; Proceedings of the 8th Machine Learning for Healthcare Conference, PMLR 219:548-564

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A Deep Learning Based Framework for Joint Image Registration and Segmentation of Brain Metastases on Magnetic Resonance Imaging

Jay Patel, Syed Rakin Ahmed, Ken Chang, Praveer Singh, Mishka Gidwani, Katharina Hoebel, Albert Kim, Christopher Bridge, Chung-Jen Teng, Xiaomei Li, Gongwen Xu, Megan McDonald, Ayal Aizer, Wenya Linda Bi, Ina Ly, Bruce Rosen, Priscilla Brastianos, Raymond Huang, Elizabeth Gerstner, Jayashree Kalpathy-Cramer; Proceedings of the 8th Machine Learning for Healthcare Conference, PMLR 219:565-587

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AIRIVA: A Deep Generative Model of Adaptive Immune Repertoires

Melanie F. Pradier, Niranjani Prasad, Paidamoyo Chapfuwa, Sahra Ghalebikesabi, Maximilian Ilse, Steven Woodhouse, Rebecca Elyanow, Javier Zazo, Javier Gonzalez Hernandez, Julia Greissl, Edward Meeds; Proceedings of the 8th Machine Learning for Healthcare Conference, PMLR 219:588-611

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EASL: A Framework for Designing, Implementing, and Evaluating ML Solutions in Clinical Healthcare Settings

Eric Prince, Todd C. Hankinson, Carsten Görg; Proceedings of the 8th Machine Learning for Healthcare Conference, PMLR 219:612-630

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Generating more faithful and consistent SOAP notes using attribute-specific parameters

Sanjana Ramprasad, Elisa Ferracane, Sai P. Selvaraj; Proceedings of the 8th Machine Learning for Healthcare Conference, PMLR 219:631-649

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Retrieval Augmented Chest X-Ray Report Generation using OpenAI GPT models

Mercy Ranjit, Gopinath Ganapathy, Ranjit Manuel, Tanuja Ganu; Proceedings of the 8th Machine Learning for Healthcare Conference, PMLR 219:650-666

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Neurological Prognostication of Post-Cardiac-Arrest Coma Patients Using EEG Data: A Dynamic Survival Analysis Framework with Competing Risks

Xiaobin Shen, Jonathan Elmer, George H. Chen; Proceedings of the 8th Machine Learning for Healthcare Conference, PMLR 219:667-690

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Efficient Representation Learning for Healthcare with Cross-Architectural Self-Supervision

Pranav Singh, Jacopo Cirrone; Proceedings of the 8th Machine Learning for Healthcare Conference, PMLR 219:691-711

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Region-based Saliency Explanations on the Recognition of Facial Genetic Syndromes

Ömer Sümer, Rebekah L. Waikel, Suzanna E. Ledgister Hanchard, Dat Duong, Peter Krawitz, Cristina Conati, Benjamin D. Solomon, Elisabeth André; Proceedings of the 8th Machine Learning for Healthcare Conference, PMLR 219:712-736

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Robust Semi-supervised Detection of Hands in Diverse Open Surgery Environments

Pranav Vaid, Serena Yeung, Anita Rau; Proceedings of the 8th Machine Learning for Healthcare Conference, PMLR 219:736-753

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Jointly Extracting Interventions, Outcomes, and Findings from RCT Reports with LLMs

Somin Wadhwa, Jay DeYoung, Benjamin Nye, Silvio Amir, Byron C. Wallace; Proceedings of the 8th Machine Learning for Healthcare Conference, PMLR 219:754-771

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Learning functional sections in medical conversations: iterative pseudo-labeling and human-in-the-loop approach

Mengqian Wang, Ilya Valmianski, Xavier Amatriain, Anitha Kannan; Proceedings of the 8th Machine Learning for Healthcare Conference, PMLR 219:772-787

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Sample-Specific Debiasing for Better Image-Text Models

Peiqi Wang, Yingcheng Liu, Ching-Yun Ko, William M. Wells, Seth Berkowitz, Steven Horng, Polina Golland; Proceedings of the 8th Machine Learning for Healthcare Conference, PMLR 219:788-803

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Are Large Language Models Ready for Healthcare? A Comparative Study on Clinical Language Understanding

Yuqing Wang, Yun Zhao, Linda Petzold; Proceedings of the 8th Machine Learning for Healthcare Conference, PMLR 219:804-823

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Characterizing personalized effects of family information on disease risk using graph representation learning

Sophie Wharrie, Zhiyu Yang, Andrea Ganna, Samuel Kaski; Proceedings of the 8th Machine Learning for Healthcare Conference, PMLR 219:824-845

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Scaling Clinical Trial Matching Using Large Language Models: A Case Study in Oncology

Cliff Wong, Sheng Zhang, Yu Gu, Christine Moung, Jacob Abel, Naoto Usuyama, Roshanthi Weerasinghe, Brian Piening, Tristan Naumann, Carlo Bifulco, Hoifung Poon; Proceedings of the 8th Machine Learning for Healthcare Conference, PMLR 219:846-862

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UDAMA: Unsupervised Domain Adaptation through Multi-discriminator Adversarial Training with Noisy Labels Improves Cardio-fitness Prediction

Yu Wu, Dimitris Spathis, Hong Jia, Ignacio Perez-Pozuelo, Tomas I. Gonzales, Soren Brage, Nicholas Wareham, Cecilia Mascolo; Proceedings of the 8th Machine Learning for Healthcare Conference, PMLR 219:863-883

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Interpretable (not just posthoc-explainable) heterogeneous survivors bias-corrected treatment effects for assignment of postdischarge interventions to prevent readmissions

Hongjing Xia, Joshua C. Chang, Sarah Nowak, Sonya Mahajan, Rohit Mahajan, Ted L. Chang, Carson C. Chow; Proceedings of the 8th Machine Learning for Healthcare Conference, PMLR 219:884-905

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Uncovering the Varied Impact of Behavioral Change Messages on Population Groups

Jiaai Xu, Rada Mihalcea, Elena Frank, Srijan Sen, Maggie Makar; Proceedings of the 8th Machine Learning for Healthcare Conference, PMLR 219:906-922

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Semi-supervised Meta-learning for Multi-source Heterogeneity in Time-series Data

Lida Zhang, Bobak J. Mortazavi; Proceedings of the 8th Machine Learning for Healthcare Conference, PMLR 219:923-941

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Dialogue-Contextualized Re-ranking for Medical History-Taking

Jian Zhu, Ilya Valmianski, Anitha Kannan; Proceedings of the 8th Machine Learning for Healthcare Conference, PMLR 219:942-958

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