Machine Learning for Health (ML4H) 2024

Helen 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 Argaw, Haoran Zhang; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:1-13

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The Human Values Project

Isaac S. Kohane; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:14-18

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The (lack of?) Science of Machine Learning for Healthcare

Matthew McDermott; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:19-29

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MIK: Modified Isolation Kernel for Biological Sequence Visualization, Classification, and Clustering

Sarwan Ali, Prakash Chourasia, Haris Mansoor, Bipin Koirala, Murray Patterson; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:30-47

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The Self-Supervision Regime and Encoder Fit for Histopathology Image Analysis

Asfandyar Azhar; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:48-60

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Modeling Clinical Decision Variability in Explainable Multimodal Seizure Detection

Asfandyar Azhar, Amulyal Mathur, Sahil Jain, James Emilian, Shaurjya Mandal, Nidhish Shah, Yongjie Jessica Zhang; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:61-72

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Mapping Three-Dimensional Tumor Heterogeneity through Deep Learning Inference of Spatial Transcriptomics from Routine Histopathology: A Proof-of-Concept Comparative Study

Zarif Azher, Gokul Srinivasan, Keluo Yao, Minh-Khang Le, Ken Lau, Harsimran Kaur, Fred Kolling, Louis Vaickus, Xiaoying Lu, Joshua Levy; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:73-85

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RESIST: Remapping EIT Signals Using Implicit Spatially-Aware Transformer

Dominik Becker, Anita Just, Günter Hahn, Peter Herrmann, Leif Saager, Fabian H. Sinz; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:86-103

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Labrador: Exploring the limits of masked language modeling for laboratory data

David Bellamy, Bhawesh Kumar, Cindy Wang, Andrew Beam; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:104-129

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Continuity Contrastive Representations of ECG for Heart Block Detection from Only Lead-I

Teya Bergamaschi, Collin Stultz, Ridwan Alam; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:130-142

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MLV2-Net: Rater-Based Majority-Label Voting for Consistent Meningeal Lymphatic Vessel Segmentation

Fabian 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; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:143-153

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Development of Machine Learning Classifiers for Blood-based Diagnosis and Prognosis of Suspected Acute Infections and Sepsis

Ljubomir Buturovic, Michael Mayhew, Roland Luethy, Kirindi Choi, Uros Midic, Nandita Damaraju, Yehudit Hasin-Brumshtein, Amitesh Pratap, Rhys Adams, Joao Fonseca, Ambika Srinath, Paul Fleming, Claudia Pereira, Oliver Liesenfeld, Purvesh Khatri, Timothy Sweeney; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:154-170

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MpoxVLM: A Vision-Language Model for Diagnosing Skin Lesions from Mpox Virus Infection

Xu Cao, Wenqian Ye, Kenny Moise, Megan Coffee; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:171-185

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wav2sleep: A Unified Multi-Modal Approach to Sleep Stage Classification from Physiological Signals

Jonathan F. Carter, Lionel Tarassenko; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:186-202

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U-Fair: Uncertainty-based Multimodal Multitask Learning for Fairer Depression Detection

Jiaee Cheong, Aditya Bangar, Sinan Kalkan, Hatice Gunes; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:203-218

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Multimodal Classification of Alzheimer’s Disease by Combining Facial and Eye-Tracking Data

Shih-Han Chou, Miini Teng, Harshinee Sriram, Chuyuan Li, Giuseppe Carenini, Cristina Conati, Thalia S. Field, Hyeju Jang, Gabriel Murray; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:219-232

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Reducing Poisson error can offset classification error: a technique to meet clinical performance requirements

Charles B. Delahunt, Courosh Mehanian, Matthew P. Horning; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:233-247

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Uncertainty Quantification for Conditional Treatment Effect Estimation under Dynamic Treatment Regimes

Leon Deng, Hong Xiong, Feng Wu, Sanyam Kapoor, Soumya Gosh, Zach Shahn, Li-wei Lehman; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:248-266

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Evaluating Safety of Large Language Models for Patient-facing Medical Question Answering

Yella Diekmann, Chase M Fensore, Rodrigo M Carrillo-Larco, Nishant Pradhan, Bhavya Appana, Joyce C Ho; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:267-290

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EHRMamba: Towards Generalizable and Scalable Foundation Models for Electronic Health Records

Adibvafa Fallahpour, Mahshid Alinoori, Wenqian Ye, Xu Cao, Arash Afkanpour, Amrit Krishnan; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:291-307

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An Interoperable Machine Learning Pipeline for Pediatric Obesity Risk Estimation

Hamed Fayyaz, Mehak Gupta, Alejandra Perez Ramirez, Claudine Jurkovitz, H. Timothy Bunnell, Thao-Ly T. Phan, Rahmatollah Beheshti; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:308-324

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Learning Explainable Treatment Policies with Clinician-Informed Representations: A Practical Approach

Johannes O Ferstad, Emily B Fox, David Scheinker, Ramesh Johari; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:325-349

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Robust Real-Time Mortality Prediction in the Intensive Care Unit using Temporal Difference Learning

Thomas Frost, Kezhi Li, Steve Harris; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:350-363

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Query-Guided Self-Supervised Summarization of Nursing Notes

Ya Gao, Hans Moen, Saila Koivusalo, Miika Koskinen, Pekka Marttinen; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:364-383

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BulkRNABert: Cancer prognosis from bulk RNA-seq based language models

Maxence Gélard, Guillaume Richard, Thomas Pierrot, Paul-Henry Cournède; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:384-400

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Are Time Series Foundation Models Ready for Vital Sign Forecasting in Healthcare?

Xiao Gu, Yu Liu, Zaineb Mohsin, Jonathan Bedford, Anshul Thakur, Peter Watkinson, Lei Clifton, Tingting Zhu, David Clifton; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:401-419

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Uncovering Judgment Biases in Emergency Triage: A Public Health Approach Based on Large Language Models

Ariel Guerra-Adames, Marta Avalos-Fernandez, Océane Doremus, Cédric Gil-Jardiné, Emmanuel Lagarde; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:420-439

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Multi-Modal Self-Supervised Learning for Surgical Feedback Effectiveness Assessment

Arushi Gupta, Rafal Dariusz Kocielnik, Jiayun Wang, Firdavs Nasriddinov, Cherine Yang, Elyssa Wong, Anima Anandkumar, Andrew Hung; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:440-455

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Training-Aware Risk Control for Intensity Modulated Radiation Therapies Quality Assurance with Conformal Prediction

Kevin He, David Adam, Sarah Han-Oh, Anqi Liu; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:456-470

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A Study on Context Length and Efficient Transformers for Biomedical Image Analysis

Sarah M. Hooper, Hui Xue; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:471-489

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Enhancing 3D Cardiac CT Segmentation with Latent Diffusion Model and Self-Supervised Learning

Quanqi Hu, Ashok Vardhan Addala, Masaki Ikuta, Ravi Soni, Gopal Avinash; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:490-501

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HIST-AID: Leveraging Historical Patient Reports for Enhanced Multi-Modal Automatic Diagnosis

Haoxu Huang, Cem Deniz, Kyunghyun Cho, Sumit Chopra, Divyam Madaan; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:502-523

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Rethinking RGB-D Fusion for Semantic Segmentation in Surgical Datasets

Muhammad Abdullah Jamal, Omid Mohareri; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:524-534

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Fundus Image-based Visual Acuity Assessment with PAC-Guarantees

Sooyong Jang, Kuk Jin Jang, Hyonyoung Choi, Yong-Seop Han, Seongjin Lee, Jin-hyun Kim, Insup Lee; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:535-549

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ST2S-rPPG: A Spatiotemporal Two-Stage Learning Approach for Pulse Estimation Using Video

Eirini Kateri, Katayoun Farrahi; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:550-562

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Meta-Analysis with Untrusted Data

Shiva Kaul, Geoffrey Gordon; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:563-593

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HeartMAE: Advancing Cardiac MRI Analysis through Optical Flow Guided Masked Autoencoding

Vladislav Kim, Lisa Schneider, Soodeh Kalaie, Declan O’Regan, Christian Bender; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:594-609

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Towards Preventing Intimate Partner Violence by Detecting Disagreements in SMS Communications

Mahesh Babu Kommalapati, Xiao Gu, Harshit Pandey, Christie J. Rizzo, Charlene Collibee, Silvio Amir, Aarti Sathyanarayana; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:610-622

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From Isolation to Collaboration: Federated Class-Heterogeneous Learning for Chest X-Ray Classification

Pranav Kulkarni, Adway Kanhere, Paul H. Yi, Vishwa S. Parekh; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:623-635

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Are Clinical T5 Models Better for Clinical Text?

Yahan Li, Keith Harrigian, Ayah Zirikly, Mark Dredze; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:636-667

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Generalized Prompt Tuning: Adapting Frozen Univariate Time Series Foundation Models for Multivariate Healthcare Time Series

Mingzhu Liu, Angela Chen, George Chen; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:668-679

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Detecting sensitive medical responses in general purpose large language models

Daniel Lopez-Martinez, Abhishek Bafna; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:680-695

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DynamITE: Optimal time-sensitive organ offers using ITE

Alessandro Marchese, Hans de Ferrante, Jeroen Berrevoets, Sam Verboven; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:696-713

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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; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:714-734

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Path-RAG: Knowledge-Guided Key Region Retrieval for Open-ended Pathology Visual Question Answering

Awais Naeem, Tianhao Li, Huang-Ru Liao, Jiawei Xu, Aby Mammen Mathew, Zehao Zhu, Zhen Tan, Ajay Kumar Jaiswal, Raffi A. Salibian, Ziniu Hu, Tianlong Chen, Ying Ding; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:735-746

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Self-Supervised Probability Imputation to Estimate the External-Natural Cause of Injury Matrix

Pirouz Naghavi, Erica Naghavi, Gang Wang, Kanyin Liane Ong; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:747-774

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Indication Driven Autoregressive Report Generation for Cardiac Magnetic Resonance Imaging

Makiya Nakashima, Po-Hao Chen, Michael Bolen, Christopher Nguyen, W. H. Wilson Tang, Richard Grimm, Deborah Kwon, David Chen; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:775-786

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Automating Feedback Analysis in Surgical Training: Detection, Categorization, and Assessment

Firdavs Nasriddinov, Rafal Kocielnik, Arushi Gupta, Cherine Yang, Elyssa Wong, Anima Anandkumar, Andrew Hung; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:787-804

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DNAMite: Interpretable Calibrated Survival Analysis with Discretized Additive Models

Mike Van Ness, Billy Block, Madeleine Udell; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:805-823

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Topological Machine Learning for Low Data Medical Imaging

Brighton Nuwagira, Caner Korkmaz, Philmore Koung, Baris Coskunuzer; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:824-838

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Transfer Learning for Pediatric Glucose Forecasting

Alain Ryser, Chuhao Feng, Tobias Scheithauer, Marc Pfister, Marie-Anne Burckhardt, Sara Bachmann, Alexander Marx, Julia E. Vogt; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:839-860

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State space modeling of multidien cyclical progression of epilepsy

Krishnakant Saboo, Yurui Cao, Vaclav Kremen, Suguna Pappu, Philippa Karoly, Dean Freestone, Mark Cook, Gregory Worrell, Ravishankar Iyer; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:861-885

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Streamlining Clinical Trial Recruitment: A Two-Stage Zero-Shot LLM Approach with Advanced Prompting

Mozhgan Saeidi; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:886-896

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MED-OMIT: Extrinsically-Focused Evaluation Metric for Omissions in Medical Summarization

Elliot Schumacher, Daniel Rosenthal, Dhruv Naik, Varun Nair, Luladay Price, Geoffrey Tso, Anitha Kannan; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:897-922

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Estimating Counterfactual Distributions under Interference

Shiv Shankar, Ritwik Sinha, Madalina Fiterau; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:923-940

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MAIRA-Seg: Enhancing Radiology Report Generation with Segmentation-Aware Multimodal Large Language Models

Harshita 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 Hyland, Javier Alvarez-Valle; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:941-960

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CoRE-BOLD: Cross-Domain Robust and Equitable Ensemble for BOLD Signal Analysis

Vipul Kumar Singh, Jyotismita Barman, Sandeep Kumar, Jayadeva Jayadeva; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:961-975

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Barttender: An approachable & interpretable way to compare medical imaging and non-imaging data

Ayush Singla, Shakson Isaac, Chirag J Patel; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:976-990

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Learning Personalized Treatment Decisions in Precision Medicine: Disentangling Treatment Assignment Bias in Counterfactual Outcome Prediction and Biomarker Identification

Michael Vollenweider, Manuel Schürch, Chiara Rohrer, Gabriele Gut, Michael Krauthammer, Andreas Wicki; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:991-1013

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DILA: Dictionary Label Attention for Mechanistic Interpretability in High-dimensional Multi-label Medical Coding Prediction

John Wu, David Wu, Jimeng Sun; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:1014-1038

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Uncertainty Estimation in Large Vision Language Models for Automated Radiology Report Generation

Jenny Xu; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:1039-1052

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RespLLM: Unifying Audio and Text with Multimodal LLMs for Generalized Respiratory Health Prediction

Yuwei Zhang, Tong Xia, Aaqib Saeed, Cecilia Mascolo; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:1053-1066

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Uncertainty-Aware Personalized Federated Learning for Realistic Healthcare Applications

Yuwei Zhang, Tong Xia, Abhirup Ghosh, Cecilia Mascolo; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:1067-1086

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RadFlag: A Black-Box Hallucination Detection Method for Medical Vision Language Models

Serena Zhang, Sraavya Sambara, Oishi Banerjee, Julian N. Acosta, L. John Fahrner, Pranav Rajpurkar; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:1087-1103

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Towards a personalized pregnancy experience: Forecasting symptoms using graph neural networks and digital health technologies

Rui Zhu, Jennifer Yu, Stephen H. Friend, Sarah M. Goodday, Bo Wang, Anna Goldenberg; Proceedings of the 4th Machine Learning for Health Symposium, PMLR 259:1104-1120

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