MLHC 2025

44 papers

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

Guilherme Seidyo Imai Aldeia, Daniel S Herman, William La Cava

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

Mosbah Aouad, Anirudh Choudhary, Awais Farooq, Steven W Nevers, Lusine Demirkhanyan

Generating Accurate Synthetic Survival Data by Conditioning on Outcomes

Mohd Ashhad, Ricardo Henao

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

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

Marc Berndt, Andrea Agostini, Beatrice Stocker, Maria Padrutt, Silvio Daniel Brugger

Can interpretability and accuracy coexist in cancer survival analysis?

Piyush Borole, Tongjie Wang, Antonio Vergari, Ajitha Rajan

The Impact of Image Resolution on Biomedical Multimodal Large Language Models

Liangyu Chen, James Burgess, Jeffrey J Nirschl, Orr Zohar, Serena Yeung-Levy

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

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

Daphné Chopard, Sonia Laguna, Kieran Chin-Cheong, Annika Dietz, Anna Badura

MedArabiQ: Benchmarking Large Language Models on Arabic Medical Tasks

Mouath Abu Daoud, Chaimae Abouzahir, Leen Kharouf, Walid Al-Eisawi, Nizar Habash

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

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

Error Profiling of Machine Learning Models: An Exploratory Visualization

Jeffrey Feng, Al Rahrooh, Alex Bui

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

Chase M Fensore, Rodrigo M Carrillo-Larco, Megha Shah, Joyce C. Ho

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

William Han, Chaojing Duan, Michael Rosenberg, Emerson Liu, Ding Zhao

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

Hongtao Hao, Vivek Prabhakaran, Veena A Nair, Nagesh Adluru, Joseph Austerweil

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

Nikkie Hooman, Zhongjie Wu, Eric C. Larson, Mehak Gupta

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

Baraa Al Jorf, Farah E. Shamout

Enhancing Adaptive Behavioral Interventions with LLM Inference from Participant Described States

Karine Karine, Benjamin M. Marlin

ADHAM: Additive Deep Hazard Analysis Mixtures for Interpretable Survival Regression

Mert Ketenci, Vincent Jeanselme, Harry Reyes Nieva, Shalmali Joshi, Noemie Elhadad

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

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

Dariia Kucheruk, Sam Osia, Pouria Mashouri, Elizaveta Rybnikova, Sergey Protserov

Bidirectional Hierarchical Protein Multi-Modal Representation Learning

Xuefeng Liu, Songhao Jiang, Chih-chan Tien, Jinbo Xu, Rick L. Stevens

ScaffoldGPT: A Scaffold-based GPT Model for Drug Optimization

Xuefeng Liu, Songhao Jiang, Ian Foster, Jinbo Xu, Rick L. Stevens

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

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

Monica Munnangi, Akshay Swaminathan, Jason Alan Fries, Jenelle A Jindal, Sanjana Narayanan

Improving ARDS Diagnosis Through Context-Aware Concept Bottleneck Models

Anish Narain, Ritam Majumdar, Nikita Narayanan, Dominic C Marshall, Sonali Parbhoo

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

Fahmida Liza Piya, Rahmatollah Beheshti

Clinicians’ Voice: Fundamental Considerations for XAI in Healthcare

Tabea Elina Röber, Rob Goedhart, Ilker Birbil

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

Elliot Schumacher, Dhruv Naik, Anitha Kannan

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

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

Predicting the Predictable in the Psychiatric High Risk

Eric Strobl

Switching State Space Modeling via Constrained Inference for Clinical Outcome Prediction

Arnold Su, Anna Wong, Fareed Sheriff, Ardavan Saeedi, Li-wei H. Lehman

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

Minghui Sun, Matthew M. Engelhard, Benjamin Goldstein

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

Biomedical Hypothesis Explainability with Graph-Based Context Retrieval

Ilya Tyagin, Saeideh Valipour, Aliaksandra Sikirzhytskaya, Michael Shtutman, Ilya Safro

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

Asim Ukaye, Numan Saeed, Karthik Nandakumar

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

Shashank Yadav, Vignesh Subbian

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

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

Han Yu, Huiyuan Yang, Akane Sano

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

Sihang Zeng, Lucas Jing Liu, Jun Wen, Meliha Yetisgen, Ruth Etzioni

INSIGHT: Explainable Weakly-Supervised Medical Image Analysis

Wenbo Zhang, Junyu Chen, Christopher Kanan

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

Yuankang Zhao, Matthew M. Engelhard