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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 298: Machine Learning for Healthcare Conference, 15-16 August 2025, Mayo Clinic, Rochester, MN, USA

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Editors: Monica Agrawal, Kaivalya Deshpande, Matthew Engelhard, Shalmali Joshi, Shengpu Tang, Iñigo Urteaga

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Balancing Interpretability and Flexibility in Modeling Diagnostic Trajectories with an Embedded Neural Hawkes Process Model

; Proceedings of the 10th Machine Learning for Healthcare Conference, PMLR 298:

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INSIGHT: Explainable Weakly-Supervised Medical Image Analysis

Wenbo Zhang, Junyu Chen, Christopher Kanan; Proceedings of the 10th Machine Learning for Healthcare Conference, PMLR 298:

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TrajSurv: Learning Continuous Latent Trajectories from Electronic Health Records for Trustworthy Survival Prediction

Sihang Zeng, Lucas Jing Liu, Jun Wen, Meliha Yetisgen, Ruth Etzioni, Gang Luo; Proceedings of the 10th Machine Learning for Healthcare Conference, PMLR 298:

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LEAVES: Learning Views for Time-Series Biobehavioral Data in Contrastive Learning

Han Yu, Huiyuan Yang, Akane Sano; Proceedings of the 10th Machine Learning for Healthcare Conference, PMLR 298:

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The Geometry of Queries: Query-Based Innovations in Retrieval-Augmented Generation for Healthcare QA

Eric Yang, Jonathan Amar, Jong Ha Lee, Bhawesh Kumar, Yugang Jia; Proceedings of the 10th Machine Learning for Healthcare Conference, PMLR 298:

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Monte Carlo ExtremalMask: Uncertainty Aware Time Series Model Interpretability For Critical Care Applications

Shashank Yadav, Vignesh Subbian; Proceedings of the 10th Machine Learning for Healthcare Conference, PMLR 298:

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FIVA: Federated Inverse Variance Averaging for Universal CT Segmentation with Uncertainty Estimation

Asim Ukaye, Numan Saeed, Karthik Nandakumar; Proceedings of the 10th Machine Learning for Healthcare Conference, PMLR 298:

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Biomedical Hypothesis Explainability with Graph-Based Context Retrieval

Ilya Tyagin, Saeideh Valipour, Aliaksandra Sikirzhytskaya, Michael Shtutman, Ilya Safro; Proceedings of the 10th Machine Learning for Healthcare Conference, PMLR 298:

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Classifying Copy Number Variations Using State Space Modeling of Targeted Sequencing Data: A Case Study in Thalassemia

Austin Talbot, Alex V. Kotlar, Lavanya Rishishwar, Yue Ke; Proceedings of the 10th Machine Learning for Healthcare Conference, PMLR 298:

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Borrowing From the Future: Enhancing Early Risk Assessment through Contrastive Learning

Minghui Sun, Matthew M. Engelhard, Benjamin Goldstein; Proceedings of the 10th Machine Learning for Healthcare Conference, PMLR 298:

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Switching State Space Modeling via Constrained Inference for Clinical Outcome Prediction

Arnold Su, Anna Wong, Fareed Sheriff, Ardavan Saeedi, Li-wei H. Lehman; Proceedings of the 10th Machine Learning for Healthcare Conference, PMLR 298:

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Predicting the Predictable in the Psychiatric High Risk

Eric Strobl; Proceedings of the 10th Machine Learning for Healthcare Conference, PMLR 298:

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Stepwise Fine and Gray: Subject-Specific Variable Selection Shows When Hemodynamic Data Improves Prognostication of Comatose Post-Cardiac Arrest Patients

Xiaobin Shen, Jonathan Elmer, George H. Chen; Proceedings of the 10th Machine Learning for Healthcare Conference, PMLR 298:

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ProtoECGNet: Case-Based Interpretable Deep Learning for Multi-Label ECG Classification with Contrastive Learning

Sahil Sethi, David Chen, Thomas Statchen, Michael C. Burkhart, Nipun Bhandari, Bashar Ramadan, Brett Beaulieu-Jones; Proceedings of the 10th Machine Learning for Healthcare Conference, PMLR 298:

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Rare Disease Differential Diagnosis with Large Language Models at Scale: From Abdominal Actinomycosis to Wilson’s Disease

Elliot Schumacher, Dhruv Naik, Anitha Kannan; Proceedings of the 10th Machine Learning for Healthcare Conference, PMLR 298:

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Clinicians’ Voice: Fundamental Considerations for XAI in Healthcare

Tabea Elina Röber, Rob Goedhart, Ilker Birbil; Proceedings of the 10th Machine Learning for Healthcare Conference, PMLR 298:

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ConTextual: Improving Clinical Text Summarization in LLMs with Context-preserving Token Filtering and Knowledge Graphs

Fahmida Liza Piya, Rahmatollah Beheshti; Proceedings of the 10th Machine Learning for Healthcare Conference, PMLR 298:

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Improving ARDS Diagnosis Through Context-Aware Concept Bottleneck Models

Anish Narain, Ritam Majumdar, Nikita Narayanan, Dominic C Marshall, Sonali Parbhoo; Proceedings of the 10th Machine Learning for Healthcare Conference, PMLR 298:

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FactEHR: A Dataset for Evaluating Factuality in Clinical Notes Using LLMs

Monica Munnangi, Akshay Swaminathan, Jason Alan Fries, Jenelle A Jindal, Sanjana Narayanan, Ivan Lopez, Lucia Tu, Philip Chung, Jesutofunmi Omiye, Mehr Kashyap, Nigam Shah; Proceedings of the 10th Machine Learning for Healthcare Conference, PMLR 298:

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Patient-Specific Deep Reinforcement Learning for Automatic Replanning in Head-and-Neck Cancer Proton Therapy

Malvern Madondo, Yuan Shao, Yingzi Liu, Jun Zhou, Xiaofeng Yang, Zhen Tian; Proceedings of the 10th Machine Learning for Healthcare Conference, PMLR 298:

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ScaffoldGPT: A Scaffold-based GPT Model for Drug Optimization

Xuefeng Liu, Songhao Jiang, Ian Foster, Jinbo Xu, Rick L. Stevens; Proceedings of the 10th Machine Learning for Healthcare Conference, PMLR 298:

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Bidirectional Hierarchical Protein Multi-Modal Representation Learning

Xuefeng Liu, Songhao Jiang, Chih-chan Tien, Jinbo Xu, Rick L. Stevens; Proceedings of the 10th Machine Learning for Healthcare Conference, PMLR 298:

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Optimizing Segmentation of Neonatal Brain MRIs with Partially Annotated Multi-Label Data

Dariia Kucheruk, Sam Osia, Pouria Mashouri, Elizaveta Rybnikova, Sergey Protserov, Jaryd Hunter, Maksym Muzychenko, Jessie Ting Guo, Michael Brudno; Proceedings of the 10th Machine Learning for Healthcare Conference, PMLR 298:

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Evaluation of Multi-Agent LLMs in Multidisciplinary Team Decision-Making for Challenging Cancer Cases

Jaesik Kim, Byounghan Lee, Kyung-Ah Sohn, Dokyoon Kim, Young Chan Lee; Proceedings of the 10th Machine Learning for Healthcare Conference, PMLR 298:

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ADHAM: Additive Deep Hazard Analysis Mixtures for Interpretable Survival Regression

Mert Ketenci, Vincent Jeanselme, Harry Reyes Nieva, Shalmali Joshi, Noémie Elhadad; Proceedings of the 10th Machine Learning for Healthcare Conference, PMLR 298:

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Enhancing Adaptive Behavioral Interventions with LLM Inference from Participant Described States

Karine Karine, Benjamin M. Marlin; Proceedings of the 10th Machine Learning for Healthcare Conference, PMLR 298:

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MedPatch: Confidence-Guided Multi-Stage Fusion for Multimodal Clinical Data

Baraa Al Jorf, Farah E. Shamout; Proceedings of the 10th Machine Learning for Healthcare Conference, PMLR 298:

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Equitable Electronic Health Record Prediction with FAME: Fairness-Aware Multimodal Embedding

Nikkie Hooman, Zhongjie Wu, Eric C. Larson, Mehak Gupta; Proceedings of the 10th Machine Learning for Healthcare Conference, PMLR 298:

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Stage-Aware Event-Based Modeling (SA-EBM) for Disease Progression

Hongtao Hao, Vivek Prabhakaran, Veena A Nair, Nagesh Adluru, Joseph Austerweil; Proceedings of the 10th Machine Learning for Healthcare Conference, PMLR 298:

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ECG-Byte: A Tokenizer for End-to-End Generative Electrocardiogram Language Modeling

William Han, Chaojing Duan, Michael Rosenberg, Emerson Liu, Ding Zhao; Proceedings of the 10th Machine Learning for Healthcare Conference, PMLR 298:

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Does Domain-Specific Retrieval Augmented Generation Help LLMs Answer Consumer Health Questions?

Chase M Fensore, Rodrigo M Carrillo-Larco, Megha Shah, Joyce C. Ho; Proceedings of the 10th Machine Learning for Healthcare Conference, PMLR 298:

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Error Profiling of Machine Learning Models: An Exploratory Visualization

Jeffrey Feng, Al Rahrooh, Alex Bui; Proceedings of the 10th Machine Learning for Healthcare Conference, PMLR 298:

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Uncertainty-Aware Prediction of Parkinson’s Disease Medication Needs: A Two-Stage Conformal Prediction Approach

Ricardo Diaz-Rincon, Muxuan Liang, Adolfo Ramirez-Zamora, Benjamin Shickel; Proceedings of the 10th Machine Learning for Healthcare Conference, PMLR 298:

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Learning to Call: A Field Trial of a Collaborative Bandit Algorithm for Optimizing Call Timing in Mobile Maternal Health

Arpan Dasgupta, Mizhaan Prajit Maniyar, Awadhesh Srivastava, Sanat Kumar, Amrita Mahale, Aparna Hegde, Arun Suggala, Karthikeyan Shanmugam, Milind Tambe, Aparna Taneja; Proceedings of the 10th Machine Learning for Healthcare Conference, PMLR 298:

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MedArabiQ: Benchmarking Large Language Models on Arabic Medical Tasks

Mouath Abu Daoud, Chaimae Abouzahir, Leen Kharouf, Walid Al-Eisawi, Nizar Habash, Farah E. Shamout; Proceedings of the 10th Machine Learning for Healthcare Conference, PMLR 298:

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Towards Scalable Newborn Screening: Automated General Movement Assessment in Uncontrolled Settings

Daphné Chopard, Sonia Laguna, Kieran Chin-Cheong, Annika Dietz, Anna Badura, Sven Wellmann, Julia E Vogt; Proceedings of the 10th Machine Learning for Healthcare Conference, PMLR 298:

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Improving Out-of-distribution Human Activity Recognition via IMU-Video Cross-modal Representation Learning

Seyyed Saeid Cheshmi, Buyao Lyu, Thomas Lisko, Rajesh Rajamani, Robert A. McGovern, Yogatheesan Varatharajah; Proceedings of the 10th Machine Learning for Healthcare Conference, PMLR 298:

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The Impact of Image Resolution on Biomedical Multimodal Large Language Models

Liangyu Chen, James Burgess, Jeffrey J Nirschl, Orr Zohar, Serena Yeung-Levy; Proceedings of the 10th Machine Learning for Healthcare Conference, PMLR 298:

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Can interpretability and accuracy coexist in cancer survival analysis?

Piyush Borole, Tongjie Wang, Antonio Vergari, Ajitha Rajan; Proceedings of the 10th Machine Learning for Healthcare Conference, PMLR 298:

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PhenoRAG: Retrieval-Augmented Generation for Efficient Zero-Shot Phenotype Identification in Clinical Reports

Marc Berndt, Andrea Agostini, Beatrice Stocker, Maria Padrutt, Silvio Daniel Brugger, D Sean Froese, Daphné Chopard, Julia E Vogt; Proceedings of the 10th Machine Learning for Healthcare Conference, PMLR 298:

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State-of-the-Art Text-Prompted Medical Segmentation Models Struggle to Ground Chest CT Findings

Mohammed Baharoon, Luyang Luo, Michael Moritz, Abhinav Kumar, Sung Eun Kim, Xiaoman Zhang, Miao Zhu, Kent Kleinschmidt, Sri Sai Dinesh Jaliparthi, Sathvik Suryadevara, Rithvik Akula, Mark Marino, Wenhui Lei, Ibrahim Ethem Hamamci, Pranav Rajpurkar; Proceedings of the 10th Machine Learning for Healthcare Conference, PMLR 298:

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Generating Accurate Synthetic Survival Data by Conditioning on Outcomes

Mohd Ashhad, Ricardo Henao; Proceedings of the 10th Machine Learning for Healthcare Conference, PMLR 298:

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Early Detection of Pancreatic Cancer Using Multimodal Learning on Electronic Health Records

Mosbah Aouad, Anirudh Choudhary, Awais Farooq, Steven W Nevers, Lusine Demirkhanyan, Bhrandon Harris, Suguna Pappu, Christopher S Gondi, Ravi Iyer; Proceedings of the 10th Machine Learning for Healthcare Conference, PMLR 298:

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Iterative Learning of Computable Phenotypes for Treatment Resistant Hypertension using Large Language Models

Guilherme Seidyo Imai Aldeia, Daniel S Herman, William La Cava; Proceedings of the 10th Machine Learning for Healthcare Conference, PMLR 298:

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