Table of Contents

• A Meta-Evaluation of Faithfulness Metrics for Long-Form Hospital-Course SummarizationGriffin Adams, Jason Zuckerg, Noémie Elhadad. 2-30 [doi]
• Which Explanation Makes Sense? A Critical Evaluation of Local Explanations for Assessing Cervical Cancer RiskCélia Wafa Ayad, Thomas Bonnier, Benjamin Bosch, Jesse Read, Sonali Parbhoo. 31-49 [doi]
• Anomaly Detection in Human Brain via Inductive Learning on Temporal Multiplex NetworksAli Behrouz, Margo I. Seltzer. 50-75 [doi]
• EEG to fMRI Synthesis Benefits from Attentional Graphs of Electrode RelationshipsDavid Calhas, Rui Henriques. 76-93 [doi]
• Typed Markers and Context for Clinical Temporal Relation ExtractionCheng Cheng 0001, Jeremy C. Weiss. 94-109 [doi]
• When More is Less: Incorporating Additional Datasets Can Hurt Performance By Introducing Spurious CorrelationsRhys Compton, Lily H. Zhang, Aahlad Manas Puli, Rajesh Ranganath. 110-127 [doi]
• When More is Less: Incorporating Additional Datasets Can Hurt Performance By Introducing Spurious CorrelationsHyungrok Do, Yuxin Chang, Yoon-Sang Cho, Padhraic Smyth, Judy Zhong. 128-149 [doi]
• Privacy-preserving patient clustering for personalized federated learningsAhmed Elhussein, Gamze Gürsoy. 150-166 [doi]
• Bringing At-home Pediatric Sleep Apnea Testing Closer to Reality: A Multi-modal Transformer ApproachHamed Fayyaz, Abigail Strang, Rahmatollah Beheshti. 167-185 [doi]
• CDANs: Temporal Causal Discovery from Autocorrelated and Non-Stationary Time Series DataMuhammad Hasan Ferdous, Uzma Hasan, Md. Osman Gani. 186-207 [doi]
• Composition Counts: A Machine Learning View on Immunothrombosis using Quantitative Phase ImagingDavid Elias 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. 208-229 [doi]
• Online Unsupervised Representation Learning of Waveforms in the Intensive Care Unit via a novel cooperative framework: Spatially Resolved Temporal Networks (SpaRTEn)Faris F. Gulamali, Ashwin Sawant, Ira Hofer, Matthew A. Levin, Alexander Charney, Karandeep Singh, Benjamin S. Glicksberg, Girish N. Nadkarni. 230-247 [doi]
• Contactless Oxygen Monitoring with Radio Waves and Gated TransformerHao He, Yuan Yuan 0002, Ying-Cong Chen, Peng Cao, Dina Katabi. 248-265 [doi]
• Multi-view Modelling of Longitudinal Health Data for Improved Prognostication of Colorectal Cancer RecurrenceDanliang Ho, Mehul Motani. 265-284 [doi]
• Detecting Heart Disease from Multi-View Ultrasound Images via Supervised Attention Multiple Instance LearningZhe Huang, Benjamin S. Wessler, Michael C. Hughes. 285-307 [doi]
• Hawkes Process with Flexible Triggering KernelsYamac Alican Isik, Paidamoyo Chapfuwa, Connor Davis, Ricardo Henao. 308-320 [doi]
• Deep Metric Learning for the Hemodynamics Inference with Electrocardiogram SignalsHyewon Jeong, Collin M. Stultz, Marzyeh Ghassemi. 321-342 [doi]
• Conceptualizing Machine Learning for Dynamic Information Retrieval of Electronic Health Record NotesSharon Jiang, Shannon Shen, Monica Agrawal, Barbara Lam, Nicholas Kurtzman, Steven Horng, David R. Karger, David A. Sontag. 343-359 [doi]
• Maximum Likelihood Estimation of Flexible Survival Densities with Importance SamplingMert Ketenci, Shreyas Bhave, Noemie Elhadad, Adler J. Perotte. 360-380 [doi]
• RadGraph2: Modeling Disease Progression in Radiology Reports via Hierarchical Information ExtractionSameer Tajdin Khanna, Adam Dejl, Kibo Yoon, Steven QH Truong, Hanh Duong, Agustina Saenz, Pranav Rajpurkar. 381-402 [doi]
• DuETT: Dual Event Time Transformer for Electronic Health RecordsAlex Labach, Aslesha Pokhrel, Xiao Shi Huang, Saba Zuberi, Seung Eun Yi, Maksims Volkovs, Tomi Poutanen, Rahul G. Krishnan. 403-422 [doi]
• Learning Missing Modal Electronic Health Records with Unified Multi-modal Data Embedding and Modality-Aware AttentionKwanhyung Lee, Soojeong Lee, Sangchul Hahn, Heejung Hyun, Edward Choi, Byungeun Ahn, Joohyung Lee. 423-442 [doi]
• Coarse race data conceals disparities in clinical risk score performanceRajiv Movva, Divya Shanmugam, Kaihua Hou, Priya Pathak, John V. Guttag, Nikhil Garg 0001, Emma Pierson. 443-472 [doi]
• Reducing Contextual Bias in Cardiac Magnetic Resonance Imaging Deep Learning Using Contrastive Self-SupervisionMakiya Nakashima, Donna Salem, HW Wilson Tang, Christopher Nguyen, Tae-Hyun Hwang, Ding Zhao, Byung-Hak Kim, Deborah Kwon, David Chen. 473-488 [doi]
• ScoEHR: Generating Synthetic Electronic Health Records using Continuous-time Diffusion ModelsAhmed Ammar Naseer, Benjamin Walker 0001, Christopher Landon, Andrew Ambrosy, Marat Fudim, Nicholas Wysham, Botros Toro, Sumanth Swaminathan, Terry Lyons. 489-508 [doi]
• PrivECG: generating private ECG for end-to-end anonymizationAlexis Nolin-Lapalme, Robert Avram, Hussin Julie. 509-528 [doi]
• Updating Clinical Risk Stratification Models Using Rank-Based Compatibility: Approaches for Evaluating and Optimizing Clinician-Model Team PerformanceErkin Ötles, Brian T. Denton, Jenna Wiens. 529-547 [doi]
• TIER: Text-Image Entropy Regularization for Medical CLIP-style modelsAnil Palepu, Andrew Beam. 548-564 [doi]
• A Deep Learning Based Framework for Joint Image Registration and Segmentation of Brain Metastases on Magnetic Resonance ImagingJay B. Patel, Syed Rakin Ahmed, Ken Chang, Praveer Singh, Mishka Gidwani, Katharina Hoebel, Albert Kim, Christopher P. Bridge, Chung-Jen Teng, Xiaomei Li, Gongwen Xu, Megan McDonald, Ayal Aizer, Wenya Linda Bi, K. Ina Ly, Bruce R. Rosen, Priscilla K. Brastianos, Raymond Y. Huang, Elizabeth R. Gerstner, Jayashree Kalpathy-Cramer. 565-587 [doi]
• AIRIVA: A Deep Generative Model of Adaptive Immune RepertoiresMelanie F. Pradier, Niranjani Prasad, Paidamoyo Chapfuwa, Sahra Ghalebikesabi, Maximilian Ilse, Steven Woodhouse, Rebecca Elyanow, Javier Zazo, Javier González Hernández, Julia Greissl, Edward Meeds. 588-611 [doi]
• EASL: A Framework for Designing, Implementing, and Evaluating ML Solutions in Clinical Healthcare SettingsEric W. Prince, Todd C. Hankinson, Carsten Görg. 612-630 [doi]
• Generating more faithful and consistent SOAP notes using attribute-specific parametersSanjana Ramprasad, Elisa Ferracane, Sai P. Selvaraj. 631-649 [doi]
• Retrieval Augmented Chest X-Ray Report Generation using OpenAI GPT modelsMercy Prasanna Ranjit, Gopinath Ganapathy, Ranjit Manuel, Tanuja Ganu. 650-666 [doi]
• Neurological Prognostication of Post-Cardiac-Arrest Coma Patients Using EEG Data: A Dynamic Survival Analysis Framework with Competing RisksXiaobin Shen 0002, Jonathan Elmer, George H. Chen. 667-690 [doi]
• Efficient Representation Learning for Healthcare with Cross-Architectural Self-SupervisionPranav Singh, Jacopo Cirrone. 691-711 [doi]
• Region-based Saliency Explanations on the Recognition of Facial Genetic SyndromesÖmer Sümer, Rebekah L. Waikel, Suzanna E. Ledgister Hanchard, Dat Duong, Peter Krawitz, Cristina Conati, Benjamin D. Solomon, Elisabeth André. 712-736 [doi]
• Robust Semi-supervised Detection of Hands in Diverse Open Surgery EnvironmentsPranav Vaid, Serena Yeung, Anita Rau. 736-753 [doi]
• Jointly Extracting Interventions, Outcomes, and Findings from RCT Reports with LLMsSomin Wadhwa, Jay DeYoung, Benjamin E. Nye, Silvio Amir, Byron C. Wallace. 754-771 [doi]
• Learning functional sections in medical conversations: iterative pseudo-labeling and human-in-the-loop approachMengqian Wang, Ilya Valmianski, Xavier Amatriain, Anitha Kannan. 772-787 [doi]
• Sample-Specific Debiasing for Better Image-Text ModelsPeiqi Wang, Yingcheng Liu, Ching Yun Ko, William M. Wells III, Seth J. Berkowitz, Steven Horng, Polina Golland. 788-803 [doi]
• Are Large Language Models Ready for Healthcare? A Comparative Study on Clinical Language UnderstandingYuqing Wang, Yun Zhao 0001, Linda R. Petzold. 804-823 [doi]
• Characterizing personalized effects of family information on disease risk using graph representation learningSophie Wharrie, Zhiyu Yang, Andrea Ganna, Samuel Kaski. 824-845 [doi]
• Scaling Clinical Trial Matching Using Large Language Models: A Case Study in OncologyCliff Wong, Sheng Zhang, Yu Gu 0017, Christine Moung, Jacob Abel, Naoto Usuyama, Roshanthi Weerasinghe, Brian Piening, Tristan Naumann, Carlo Bifulco, Hoifung Poon. 846-862 [doi]
• UDAMA: Unsupervised Domain Adaptation through Multi-discriminator Adversarial Training with Noisy Labels Improves Cardio-fitness PredictionYu Wu, Dimitris Spathis, Hong Jia, Ignacio Perez-Pozuelo, Tomas I. Gonzales, Søren Brage, Nicholas J. Wareham, Cecilia Mascolo. 863-883 [doi]
• Interpretable (not just posthoc-explainable) heterogeneous survivors bias-corrected treatment effects for assignment of postdischarge interventions to prevent readmissionsHongjing Xia, Joshua C. Chang, Sarah Nowak, Sonya Mahajan, Rohit Mahajan, Ted L. Chang, Carson C. Chow. 884-905 [doi]
• Uncovering the Varied Impact of Behavioral Change Messages on Population GroupsJiaai Xu, Rada Mihalcea, Elena Frank, Srijan Sen, Maggie Makar. 906-922 [doi]
• Semi-supervised Meta-learning for Multi-source Heterogeneity in Time-series DataLida Zhang, Bobak J. Mortazavi. 923-941 [doi]
• Dialogue-Contextualized Re-ranking for Medical History-TakingJian Zhu, Ilya Valmianski, Anitha Kannan. 942-958 [doi]