Conference on Health, Inference, and Learning (CHIL) 2024

Tom Pollard, Edward Choi, Pankhuri Singhal, Michael Hughes, Elena Sizikova, Bobak Mortazavi, Irene Chen, Fei Wang, Tasmie Sarker, Matthew McDermott, Marzyeh Ghassemi; Proceedings of the fifth Conference on Health, Inference, and Learning, PMLR 248:1-6

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Interpretation of Intracardiac Electrograms Through Textual Representations

William Han, Diana Guadalupe Gomez, Avi Alok, Chaojing Duan, Michael A Rosenberg, Douglas J Weber, Emerson Liu, Ding Zhao; Proceedings of the fifth Conference on Health, Inference, and Learning, PMLR 248:7-23

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DDoS: A Graph neural Network Based Drug Synergy Prediction Algorithm

Kyriakos Schwarz, Pliego Mendieta Alicia, Amina Mollaysa, Planas-Paz Lara, Chantal Pauli, Ahmed Allam, Michael Krauthammer; Proceedings of the fifth Conference on Health, Inference, and Learning, PMLR 248:24-38

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Daily Physical Activity Monitoring: Adaptive Learning from Multi-source Motion Sensor Data

Haoting Zhang, Donglin Zhan, Yunduan Lin, Jinghai He, Qing Zhu, Zuo-Jun Shen, Zeyu Zheng; Proceedings of the fifth Conference on Health, Inference, and Learning, PMLR 248:39-54

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Enhancing Collaborative Medical Outcomes through Private Synthetic Hypercube Augmentation: PriSHA

Shinpei Nakamura Sakai, Dennis Shung, Jasjeet S Sekhon; Proceedings of the fifth Conference on Health, Inference, and Learning, PMLR 248:55-71

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Integrating ChatGPT into Secure Hospital Networks: A Case Study on Improving Radiology Report Analysis

Kyungsu Kim, Junhyun Park, Saul Langarica, Adham Mahmoud Alkhadrawi, Synho Do; Proceedings of the fifth Conference on Health, Inference, and Learning, PMLR 248:72-87

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Multiple Instance Learning with Absolute Position Information

Meera Krishnamoorthy, Jenna Wiens; Proceedings of the fifth Conference on Health, Inference, and Learning, PMLR 248:88-104

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SQUWA: Signal Quality Aware DNN Architecture for Enhanced Accuracy in Atrial Fibrillation Detection from Noisy PPG Signals

Runze Yan, Cheng Ding, Ran Xiao, Alex Fedorov, Randall J Lee, Fadi Nahab, Xiao Hu; Proceedings of the fifth Conference on Health, Inference, and Learning, PMLR 248:105-119

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An Improved Bayesian Permutation Entropy Estimator with Wasserstein-Optimized Hierarchical Priors

Zachary Blanks, Donald E Brown, Marc A Adams, Siddhartha S Angadi; Proceedings of the fifth Conference on Health, Inference, and Learning, PMLR 248:120-136

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Temporally Multi-Scale Sparse Self-Attention for Physical Activity Data Imputation

Hui Wei, Maxwell A Xu, Colin Samplawski, James Matthew Rehg, Santosh Kumar, Benjamin Marlin; Proceedings of the fifth Conference on Health, Inference, and Learning, PMLR 248:137-154

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Regularizing and Interpreting Vision Transformer by Patch Selection on Echocardiography Data

Alfred Nilsson, Hossein Azizpour; Proceedings of the fifth Conference on Health, Inference, and Learning, PMLR 248:155-168

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A Machine Learning Approach for Predicting Upper Limb Motion Intentions with Multimodal Data

Pavan Uttej Ravva, Pinar Kullu, Mohammad Fahim Abrar, Roghayeh Leila Barmaki; Proceedings of the fifth Conference on Health, Inference, and Learning, PMLR 248:169-181

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From Basic to Extra Features: Hypergraph Transformer Pretrain-then-Finetuning for Balanced Clinical Predictions on EHR

Ran Xu, Yiwen Lu, Chang Liu, Yong Chen, Yan Sun, Xiao Hu, Joyce C Ho, Carl Yang; Proceedings of the fifth Conference on Health, Inference, and Learning, PMLR 248:182-197

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Explainable and Privacy-Preserving Machine Learning via Domain-Aware Symbolic Regression

Kei Sen Fong, Mehul Motani; Proceedings of the fifth Conference on Health, Inference, and Learning, PMLR 248:198-216

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Simulation of Health Time Series with Nonstationarity

Adedolapo Aishat Toye, Louis Gomez, Samantha Kleinberg; Proceedings of the fifth Conference on Health, Inference, and Learning, PMLR 248:217-232

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Brain-Mamba: Encoding Brain Activity via Selective State Space Models

Ali Behrouz, Farnoosh Hashemi; Proceedings of the fifth Conference on Health, Inference, and Learning, PMLR 248:233-250

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Data-driven Subgrouping of Patient Trajectories with Chronic Diseases: Evidence from Low Back Pain

Christof Friedrich Naumzik, Alice Kongsted, Werner Vach, Stefan Feuerriegel; Proceedings of the fifth Conference on Health, Inference, and Learning, PMLR 248:251-279

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Vision-Language Generative Model for View-Specific Chest X-ray Generation

Hyungyung Lee, Da Young Lee, Wonjae Kim, Jin-Hwa Kim, Tackeun Kim, Jihang Kim, Leonard Sunwoo, Edward Choi; Proceedings of the fifth Conference on Health, Inference, and Learning, PMLR 248:280-296

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FAMEWS: a Fairness Auditing tool for Medical Early-Warning Systems

Marine Hoche, Olga Mineeva, Manuel Burger, Alessandro Blasimme, Gunnar Ratsch; Proceedings of the fifth Conference on Health, Inference, and Learning, PMLR 248:297-311

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Unsupervised Domain Adaptation for Medical Image Segmentation with Dynamic Prototype-based Contrastive Learning

Qing En, Yuhong Guo; Proceedings of the fifth Conference on Health, Inference, and Learning, PMLR 248:312-325

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FlowCyt: A Comparative Study of Deep Learning Approaches for Multi-Class Classification in Flow Cytometry Benchmarking

Lorenzo Bini, Fatemeh Nassajian Mojarrad, Margarita Liarou, Thomas Matthes, Stephane Marchand-Maillet; Proceedings of the fifth Conference on Health, Inference, and Learning, PMLR 248:326-338

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A Data-Centric Approach To Generate Faithful and High Quality Patient Summaries with Large Language Models

Stefan Hegselmann, Zejiang Shen, Florian Gierse, Monica Agrawal, David Sontag, Xiaoyi Jiang; Proceedings of the fifth Conference on Health, Inference, and Learning, PMLR 248:339-379

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Addressing Wearable Sleep Tracking Inequity: A New Dataset and Novel Methods for a Population with Sleep Disorders

Will Ke Wang, Jiamu Yang, Leeor Hershkovich, Hayoung Jeong, Bill Chen, Karnika Singh, Ali R Roghanizad, Md Mobashir Hasan Shandhi, Andrew R Spector, Jessilyn Dunn; Proceedings of the fifth Conference on Health, Inference, and Learning, PMLR 248:380-396

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FETCH: A Fast and Efficient Technique for Channel Selection in EEG Wearable Systems

Alireza Amirshahi, Jonathan Dan, Jose Angel Miranda, Amir Aminifar, David Atienza; Proceedings of the fifth Conference on Health, Inference, and Learning, PMLR 248:397-409

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Interpretable breast cancer classification using CNNs on mammographic images

Ann-Kristin Balve, Peter Hendrix; Proceedings of the fifth Conference on Health, Inference, and Learning, PMLR 248:410-426

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Using Expert Gaze for Self-Supervised and Supervised Contrastive Learning of Glaucoma from OCT Data

Wai Tak Lau, Ye Tian, Roshan Kenia, Saanvi Aima, Kaveri A Thakoor; Proceedings of the fifth Conference on Health, Inference, and Learning, PMLR 248:427-445

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Tuning In: Comparative Analysis of Audio Classifier Performance in Clinical Settings with Limited Data

Hamza Mahdi, Eptehal Nashnoush, Rami Saab, Arjun Balachandar, Rishit Dagli, Lucas Perri, Houman Khosravani; Proceedings of the fifth Conference on Health, Inference, and Learning, PMLR 248:446-460

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s-SuStaIn: Scaling subtype and stage inference via simultaneous clustering of subjects and biomarkers

Raghav Tandon, James J Lah, Cassie S Mitchell; Proceedings of the fifth Conference on Health, Inference, and Learning, PMLR 248:461-476

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Regulating AI Adaptation: An Analysis of AI Medical Device Updates

Kevin Wu, Eric Wu, Kit Rodolfa, Daniel E Ho, James Zou; Proceedings of the fifth Conference on Health, Inference, and Learning, PMLR 248:477-488

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Retrieving Evidence from EHRs with LLMs: Possibilities and Challenges

Hiba Ahsan, Denis Jered McInerney, Jisoo Kim, Christopher A Potter, Geoffrey Young, Silvio Amir, Byron C Wallace; Proceedings of the fifth Conference on Health, Inference, and Learning, PMLR 248:489-505

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Development of Error Passing Network for Optimizing the Prediction of VO$_2$ peak in Childhood Acute Leukemia Survivors

Nicolas Raymond, Hakima Laribi, Maxime Caru, Mehdi Mitiche, Valerie Marcil, Maja Krajinovic, Daniel Curnier, Daniel Sinnett, Martin Vallières; Proceedings of the fifth Conference on Health, Inference, and Learning, PMLR 248:506-521

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Health-LLM: Large Language Models for Health Prediction via Wearable Sensor Data

Yubin Kim, Xuhai Xu, Daniel McDuff, Cynthia Breazeal, Hae Won Park; Proceedings of the fifth Conference on Health, Inference, and Learning, PMLR 248:522-539

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Dynamic Survival Analysis for Early Event Prediction

Hugo Yèche, Manuel Burger, Dinara Veshchezerova, Gunnar Ratsch; Proceedings of the fifth Conference on Health, Inference, and Learning, PMLR 248:540-557

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Contextual Unsupervised Deep Clustering in Digital Pathology

Mariia Sidulova, Seyed Kahaki, Ian Hagemann, Alexej Gossmann; Proceedings of the fifth Conference on Health, Inference, and Learning, PMLR 248:558-565

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DoseMate: A Real-world Evaluation of Machine Learning Classification of Pill Taking Using Wrist-worn Motion Sensors

Antoine Nzeyimana, Anthony Campbell, James M Scanlan, Joanne D Stekler, Jenna Marquard, Barry G Saver, Jeremy Gummeson; Proceedings of the fifth Conference on Health, Inference, and Learning, PMLR 248:566-581

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Systematic Evaluation of Self-Supervised Learning Approaches for Wearable-Based Fatigue Recognition

Tamás Visy, Rita Kuznetsova, Christian Holz, Shkurta Gashi; Proceedings of the fifth Conference on Health, Inference, and Learning, PMLR 248:582-596

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Adaptive Interventions with User-Defined Goals for Health Behavior Change

Aishwarya Mandyam, Matthew Jörke, William Denton, Barbara E. Engelhardt, Emma Brunskill; Proceedings of the fifth Conference on Health, Inference, and Learning, PMLR 248:597-618

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Algorithmic Changes Are Not Enough: Evaluating the Removal of Race Adjustment From the eGFR Equation

Marika M Cusick, Glenn M Chertow, Douglas K Owens, Michelle Y Williams, Sherri Rose; Proceedings of the fifth Conference on Health, Inference, and Learning, PMLR 248:619-643

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A cross-study Analysis of Wearable Datasets and the Generalizability of Acute Illness Monitoring Models

Patrick Kasl, Severine Soltani, Lauryn Keeler Bruce, Varun Kumar Viswanath, Wendy Hartogensis, Amarnath Gupta, Ilkay Altintas, Stephan Dilchert, Frederick M Hecht, Ashley Mason, Benjamin L Smarr; Proceedings of the fifth Conference on Health, Inference, and Learning, PMLR 248:644-682

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Learning Social Fairness Preferences from Non-Expert Stakeholder Opinions in Kidney Placement

Mukund Telukunta, Sukruth Rao, Gabriella Stickney, Venkata Sriram Siddhardh Nadendla, Casey Canfield; Proceedings of the fifth Conference on Health, Inference, and Learning, PMLR 248:683-695

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