Table of Contents

• Machine Learning for Health (ML4H) 2024Helen Zhou, Stefan Hegselmann, Elizabeth Healey, Trenton Chang, Caleb Ellington, Michael Leone, Vishwali Mhasawade, Sana Tonekaboni, Winston Chen, Hyewon Jeong, Xiaoxiao Li, Juyeon Heo, Payal Chandak, Ayush Noori, Sarah Jabbour, Jessica Dafflon, Jerry Ji, Jivat Neet Kaur, Amin Adibi, Xu Cao, Meera Krishnamoorthy, Yidi Huang, Fabian Gröger, Aishwarya Mandyam, Niloufar Saharhkhiz, Teya Bergamaschi, William Boag, Jeroen Berrevoets, Matthew Lee, Kyle Heuton, Peniel N. Argaw, Haoran Zhang. 1-13 [doi]
• The Human Values ProjectIsaac S. Kohane. 14-18 [doi]
• The (lack of?) Science of Machine Learning for HealthcareMatthew McDermott. 19-29 [doi]
• MIK: Modified Isolation Kernel for Biological Sequence Visualization, Classification, and ClusteringSarwan Ali, Prakash Chourasia, Haris Mansoor, Bipin Koirala, Murray Patterson. 30-47 [doi]
• The Self-Supervision Regime and Encoder Fit for Histopathology Image AnalysisAsfandyar Azhar. 48-60 [doi]
• Modeling Clinical Decision Variability in Explainable Multimodal Seizure DetectionAsfandyar Azhar, Amulyal Mathur, Sahil Jain, James Emilian, Shaurjya Mandal, Nidhish Shah, Yongjie Jessica Zhang. 61-72 [doi]
• Mapping Three-Dimensional Tumor Heterogeneity through Deep Learning Inference of Spatial Transcriptomics from Routine Histopathology: A Proof-of-Concept Comparative StudyZarif L. Azher, Gokul Srinivasan, Keluo Yao, Minh-Khang Le, Ken Lau, Harsimran Kaur, Fred Kolling, Louis J. Vaickus, Xiaoying Lu, Joshua J. Levy. 73-85 [doi]
• RESIST: Remapping EIT Signals Using Implicit Spatially-Aware TransformerDominik Becker, Anita Just, Günter Hahn, Peter Herrmann, Leif Saager, Fabian H. Sinz. 86-103 [doi]
• Labrador: Exploring the limits of masked language modeling for laboratory dataDavid R. Bellamy, Bhawesh Kumar, Cindy Wang, Andrew Beam. 104-129 [doi]
• Continuity Contrastive Representations of ECG for Heart Block Detection from Only Lead-ITeya S. Bergamaschi, Collin M. Stultz, Ridwan Alam. 130-142 [doi]
• MLV2-Net: Rater-Based Majority-Label Voting for Consistent Meningeal Lymphatic Vessel SegmentationFabian Bongratz, Markus Karmann, Adrian Holz, Moritz Bonhoeffer, Viktor Neumaier, Sarah Deli, Benita Schmitz-Koep, Claus Zimmer, Christian Sorg, Melissa Thalhammer, Dennis M. Hedderich, Christian Wachinger. 143-153 [doi]
• Development of Machine Learning Classifiers for Blood-based Diagnosis and Prognosis of Suspected Acute Infections and SepsisLjubomir J. Buturovic, Michael B. Mayhew, Roland Lüthy, Kirindi Choi, Uros Midic, Nandita Damaraju, Yehudit Hasin-Brumshtein, Amitesh Pratap, Rhys M. Adams, João F. Henriques, Ambika Srinath, Paul Fleming, Claudia Pereira, Oliver Liesenfeld, Purvesh Khatri, Timothy Sweeney. 154-170 [doi]
• MpoxVLM: A Vision-Language Model for Diagnosing Skin Lesions from Mpox Virus InfectionXu Cao, Wenqian Ye, Kenny Moise, Megan Coffee. 171-185 [doi]
• wav2sleep: A Unified Multi-Modal Approach to Sleep Stage Classification from Physiological SignalsJonathan F. Carter, Lionel Tarassenko. 186-202 [doi]
• U-Fair: Uncertainty-based Multimodal Multitask Learning for Fairer Depression DetectionJiaee Cheong, Aditya Bangar, Sinan Kalkan, Hatice Gunes. 203-218 [doi]
• Multimodal Classification of Alzheimer's Disease by Combining Facial and Eye-Tracking DataShih-Han Chou, Miini Teng, Harshinee Sriram, Chuyuan Li, Giuseppe Carenini, Cristina Conati, Thalia Shoshana Field, Hyeju Jang, Gabriel Murray. 219-232 [doi]
• Reducing Poisson error can offset classification error: a technique to meet clinical performance requirementsCharles B. Delahunt, Courosh Mehanian, Matthew P. Horning. 233-247 [doi]
• Uncertainty Quantification for Conditional Treatment Effect Estimation under Dynamic Treatment RegimesLeon Deng, Hong Xiong, Feng Wu, Sanyam Kapoor, Soumya Gosh, Zach Shahn, Li-Wei H. Lehman. 248-266 [doi]
• Evaluating Safety of Large Language Models for Patient-facing Medical Question AnsweringYella Diekmann, Chase Fensore, Rodrigo M. Carrillo-Larco, Nishant Pradhan, Bhavya Appana, Joyce C. Ho. 267-290 [doi]
• EHRMamba: Towards Generalizable and Scalable Foundation Models for Electronic Health RecordsAdibvafa Fallahpour, Mahshid Alinoori, Wenqian Ye, Xu Cao, Arash Afkanpour, Amrit Krishnan. 291-307 [doi]
• An Interoperable Machine Learning Pipeline for Pediatric Obesity Risk EstimationHamed Fayyaz, Mehak Gupta, Alejandra Perez Ramirez, Claudine Jurkovitz, H. Timothy Bunnell, Thao-Ly T. Phan, Rahmatollah Beheshti. 308-324 [doi]
• Learning Explainable Treatment Policies with Clinician-Informed Representations: A Practical ApproachJohannes O. Ferstad, Emily B. Fox, David Scheinker, Ramesh Johari. 325-349 [doi]
• Robust Real-Time Mortality Prediction in the Intensive Care Unit using Temporal Difference LearningThomas Frost, Kezhi Li, Steve Harris. 350-363 [doi]
• Query-Guided Self-Supervised Summarization of Nursing NotesYa Gao 0005, Hans Moen, Saila Koivusalo, Miika Koskinen, Pekka Marttinen. 364-383 [doi]
• BulkRNABert: Cancer prognosis from bulk RNA-seq based language modelsMaxence Gélard, Guillaume Richard, Thomas Pierrot, Paul-Henry Cournède. 384-400 [doi]
• Are Time Series Foundation Models Ready for Vital Sign Forecasting in Healthcare?Xiao Gu 0003, Yu Liu, Zaineb Mohsin, Jonathan Bedford, Anshul Thakur, Peter J. Watkinson, Lei A. Clifton, Tingting Zhu 0001, David A. Clifton. 401-419 [doi]
• Uncovering Judgment Biases in Emergency Triage: A Public Health Approach Based on Large Language ModelsAriel Guerra-Adames, Marta Avalos Fernandez, Oceane Doremus, Cédric Gil-Jardiné, Emmanuel Lagarde. 420-439 [doi]
• Multi-Modal Self-Supervised Learning for Surgical Feedback Effectiveness AssessmentArushi Gupta, Rafal Kocielnik, Jiayun Wang, Firdavs Nasriddinov, Cherine Yang, Elyssa Y. Wong, Anima Anandkumar, Andrew J. Hung. 440-455 [doi]
• Training-Aware Risk Control for Intensity Modulated Radiation Therapies Quality Assurance with Conformal PredictionKevin He, David Adam, Sarah Han-Oh, Anqi Liu. 456-470 [doi]
• A Study on Context Length and Efficient Transformers for Biomedical Image AnalysisSarah M. Hooper, Hui Xue. 471-489 [doi]
• Enhancing 3D Cardiac CT Segmentation with Latent Diffusion Model and Self-Supervised LearningQuanqi Hu, Ashok Vardhan Addala, Masaki Ikuta, Ravi Soni, Gopal Avinash. 490-501 [doi]
• HIST-AID: Leveraging Historical Patient Reports for Enhanced Multi-Modal Automatic DiagnosisHaoxu Huang, Cem M. Deniz, KyungHyun Cho, Sumit Chopra, Divyam Madaan. 502-523 [doi]
• Rethinking RGB-D Fusion for Semantic Segmentation in Surgical DatasetsMuhammad Abdullah Jamal, Omid Mohareri. 524-534 [doi]
• Fundus Image-based Visual Acuity Assessment with PAC-GuaranteesSooyong Jang, Kuk Jin Jang, Hyonyoung Choi, Yong-Seop Han, Seongjin Lee, Jin Hyun Kim, Insup Lee 0001. 535-549 [doi]
• ST2S-rPPG: A Spatiotemporal Two-Stage Learning Approach for Pulse Estimation Using VideoEirini Kateri, Katayoun Farrahi. 550-562 [doi]
• Meta-Analysis with Untrusted DataShiva Kaul, Geoffrey J. Gordon. 563-593 [doi]
• HeartMAE: Advancing Cardiac MRI Analysis through Optical Flow Guided Masked AutoencodingVladislav Kim, Lisa Schneider, Soodeh Kalaie, Declan O'Regan, Christian Bender. 594-609 [doi]
• Towards Preventing Intimate Partner Violence by Detecting Disagreements in SMS CommunicationsMahesh Babu Kommalapati, Xiao Gu, Harshit Pandey, Christie Rizzo, Charlene Collibee, Silvio Amir, Aarti Sathyanarayana. 610-622 [doi]
• From Isolation to Collaboration: Federated Class-Heterogeneous Learning for Chest X-Ray ClassificationPranav Kulkarni, Adway U. Kanhere, Paul H. Yi, Vishwa S. Parekh. 623-635 [doi]
• Are Clinical T5 Models Better for Clinical Text?Yahan Li, Keith Harrigian, Ayah Zirikly, Mark Dredze. 636-667 [doi]
• Generalized Prompt Tuning: Adapting Frozen Univariate Time Series Foundation Models for Multivariate Healthcare Time SeriesMingzhu Liu, Angela H. Chen, George H. Chen. 668-679 [doi]
• Detecting sensitive medical responses in general purpose large language modelsDaniel Lopez Martinez, Abhishek Bafna. 680-695 [doi]
• DynamITE: Optimal time-sensitive organ offers using ITEAlessandro Marchese, Hans de Ferrante, Jeroen Berrevoets, Sam Verboven. 696-713 [doi]
• How Should We Represent History in Interpretable Models of Clinical Policies?Anton Matsson, Lena Stempfle, Yaochen Rao, Zachary R. Margolin, Heather J. Litman, Fredrik D. Johansson. 714-734 [doi]
• Path-RAG: Knowledge-Guided Key Region Retrieval for Open-ended Pathology Visual Question AnsweringAwais Naeem, Tianhao Li, Huang-Ru Liao, Jiawei Xu 0006, Aby M. Mathew, Zehao Zhu, Zhen Tan 0001, Ajay Kumar Jaiswal, Raffi A. Salibian, Ziniu Hu, Tianlong Chen 0001, Ying Ding 0001. 735-746 [doi]
• Self-Supervised Probability Imputation to Estimate the External-Natural Cause of Injury MatrixPirouz Naghavi, Erica Naghavi, Gang Wang, Kanyin Liane Ong. 747-774 [doi]
• Indication Driven Autoregressive Report Generation for Cardiac Magnetic Resonance ImagingMakiya Nakashima, Po-Hao Chen 0001, Michael Bolen, Christopher Nguyen, W. H. Wilson Tang, Richard Grimm, Deborah Kwon, David Chen 0003. 775-786 [doi]
• Automating Feedback Analysis in Surgical Training: Detection, Categorization, and AssessmentFirdavs Nasriddinov, Rafal Kocielnik, Arushi Gupta, Cherine Yang, Elyssa Y. Wong, Anima Anandkumar, Andrew J. Hung. 787-804 [doi]
• DNAMite: Interpretable Calibrated Survival Analysis with Discretized Additive ModelsMike Van Ness, Billy Block, Madeleine Udell. 805-823 [doi]
• Topological Machine Learning for Low Data Medical ImagingBrighton Nuwagira, Caner Korkmaz, Philmore Koung, Baris Coskunuzer. 824-838 [doi]
• Transfer Learning for Pediatric Glucose ForecastingAlain Ryser, Chuhao Feng, Tobias Scheithauer, Marc Pfister, Marie-Anne Burckhardt, Sara Bachmann, Alexander Marx 0001, Julia E. Vogt. 839-860 [doi]
• State space modeling of multidien cyclical progression of epilepsyKrishnakant V. Saboo, Yurui Cao, Václav Kremen, Suguna Pappu, Philippa J. Karoly, Dean R. Freestone, Mark J. Cook, Gregory A. Worrell, Ravishankar K. Iyer. 861-885 [doi]
• Streamlining Clinical Trial Recruitment: A Two-Stage Zero-Shot LLM Approach with Advanced PromptingMozhgan Saeidi. 886-896 [doi]
• MED-OMIT: Extrinsically-Focused Evaluation Metric for Omissions in Medical SummarizationElliot Schumacher, Daniel Rosenthal, Dhruv Naik, Varun Nair, Luladay Price, Geoffrey J. Tso, Anitha Kannan. 897-922 [doi]
• Estimating Counterfactual Distributions under InterferenceShiv Shankar, Ritwik Sinha, Madalina Fiterau. 923-940 [doi]
• MAIRA-Seg: Enhancing Radiology Report Generation with Segmentation-Aware Multimodal Large Language ModelsHarshita Sharma, Valentina Salvatelli, Shaury Srivastav, Kenza Bouzid, Shruthi Bannur, Daniel C. Castro, Maximilian Ilse, Sam Bond-Taylor, Mercy Prasanna Ranjit, Fabian Falck, Fernando Pérez-García, Anton Schwaighofer, Hannah Richardson, Maria Wetscherek, Stephanie L. Hyland, Javier Alvarez-Valle. 941-960 [doi]
• CoRE-BOLD: Cross-Domain Robust and Equitable Ensemble for BOLD Signal AnalysisVipul Kumar Singh, Jyotismita Barman, Sandeep Kumar 0005, Jayadeva. 961-975 [doi]
• Barttender: An approachable & interpretable way to compare medical imaging and non-imaging dataAyush Singla, Shakson Isaac, Chirag J. Patel. 976-990 [doi]
• Learning Personalized Treatment Decisions in Precision Medicine: Disentangling Treatment Assignment Bias in Counterfactual Outcome Prediction and Biomarker IdentificationMichael Vollenweider, Manuel Schürch, Chiara Rohrer, Gabriele Gut, Michael Krauthammer, Andreas Wicki. 991-1013 [doi]
• DILA: Dictionary Label Attention for Mechanistic Interpretability in High-dimensional Multi-label Medical Coding PredictionJohn Wu, David Wu, Jimeng Sun 0001. 1014-1038 [doi]
• Uncertainty Estimation in Large Vision Language Models for Automated Radiology Report GenerationJenny Xu. 1039-1052 [doi]
• RespLLM: Unifying Audio and Text with Multimodal LLMs for Generalized Respiratory Health PredictionYuwei Zhang, Tong Xia, Aaqib Saeed, Cecilia Mascolo. 1053-1066 [doi]
• Uncertainty-Aware Personalized Federated Learning for Realistic Healthcare ApplicationsYuwei Zhang, Tong Xia, Abhirup Ghosh, Cecilia Mascolo. 1067-1086 [doi]
• RadFlag: A Black-Box Hallucination Detection Method for Medical Vision Language ModelsSerena Zhang, Sraavya Sambara, Oishi Banerjee, Julián Nicolás Acosta, L. John Fahrner, Pranav Rajpurkar. 1087-1103 [doi]
• Towards a personalized pregnancy experience: Forecasting symptoms using graph neural networks and digital health technologiesRui Zhu, Jennifer Yu, Stephen H. Friend, Sarah M. Goodday, Bo Wang 0044, Anna Goldenberg. 1104-1120 [doi]