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ORCIDCHIL 2024: New York, NY, USA
- Tom Pollard, Edward Choi, Pankhuri Singhal, Michael Hughes, Elena Sizikova, Bobak Mortazavi, Irene Chen, Fei Wang, Tasmie Sarker, Matthew McDermott, Marzyeh Ghassemi:
Conference on Health, Inference, and Learning, New York, NY, USA, 27-28 June 2024. Proceedings of Machine Learning Research 248, PMLR 2024 - Tom J. Pollard, Edward Choi, Pankhuri Singhal, Michael C. Hughes, Elena Sizikova, Bobak Mortazavi, Irene Y. Chen, Fei Wang, Tasmie Sarker, Matthew B. A. McDermott, Marzyeh Ghassemi:
Conference on Health, Inference, and Learning (CHIL) 2024. 1-6 - William Han, Diana Guadalupe Gomez, Avi Alok, Chaojing Duan, Michael A. Rosenberg, Douglas Weber, Emerson Liu, Ding Zhao:
Interpretation of Intracardiac Electrograms Through Textual Representations. 7-23 - Kyriakos Schwarz, Alicia Pliego-Mendieta, Amina Mollaysa, Lara Planas-Paz, Chantal Pauli, Ahmed Allam, Michael Krauthammer:
DDoS: A Graph neural Network Based Drug Synergy Prediction Algorithm. 24-38 - Haoting Zhang, Donglin Zhan, Yunduan Lin, Jinghai He, Qing Zhu, Zuo-Jun Max Shen, Zeyu Zheng:
Daily Physical Activity Monitoring: Adaptive Learning from Multi-source Motion Sensor Data. 39-54 - Shinpei Nakamura-Sakai, Dennis L. Shung, Jasjeet S. Sekhon:
Enhancing Collaborative Medical Outcomes through Private Synthetic Hypercube Augmentation: PriSHA. 55-71 - Kyungsu Kim, Junhyun Park, Saúl Langarica, Adham Mahmoud Alkhadrawi, Synho Do:
Integrating ChatGPT into Secure Hospital Networks: A Case Study on Improving Radiology Report Analysis. 72-87 - Meera Krishnamoorthy, Jenna Wiens:
Multiple Instance Learning with Absolute Position Information. 88-104 - Runze Yan, Cheng Ding, Ran Xiao, Alex Fedorov, Randall J. Lee, Fadi B. Nahab, Xiao Hu:
SQUWA: Signal Quality Aware DNN Architecture for Enhanced Accuracy in Atrial Fibrillation Detection from Noisy PPG Signals. 105-119 - Zachary Blanks, Donald E. Brown, Marc A Adams, Siddhartha S. Angadi:
An Improved Bayesian Permutation Entropy Estimator with Wasserstein-Optimized Hierarchical Priors. 120-136 - Hui Wei, Maxwell A. Xu, Colin Samplawski, James Matthew Rehg, Santosh Kumar, Benjamin M. Marlin:
Temporally Multi-Scale Sparse Self-Attention for Physical Activity Data Imputation. 137-154 - Alfred Nilsson, Hossein Azizpour:
Regularizing and Interpreting Vision Transformer by Patch Selection on Echocardiography Data. 155-168 - Pavan Uttej Ravva, Pinar Kullu, Mohammad Fahim Abrar, Roghayeh Leila Barmaki:
A Machine Learning Approach for Predicting Upper Limb Motion Intentions with Multimodal Data. 169-181 - Ran Xu, Yiwen Lu, Chang Liu, Yong Chen, Yan Sun, Xiao Hu, Joyce C. Ho, Carl Yang:
From Basic to Extra Features: Hypergraph Transformer Pretrain-then-Finetuning for Balanced Clinical Predictions on EHR. 182-197 - Kei Sen Fong, Mehul Motani:
Explainable and Privacy-Preserving Machine Learning via Domain-Aware Symbolic Regression. 198-216 - Adedolapo Aishat Toye, Louis Adedapo Gomez, Samantha Kleinberg:
Simulation of Health Time Series with Nonstationarity. 217-232 - Ali Behrouz, Farnoosh Hashemi:
Brain-Mamba: Encoding Brain Activity via Selective State Space Models. 233-250 - Christof Naumzik, Alice Kongsted, Werner Vach, Stefan Feuerriegel:
Data-driven Subgrouping of Patient Trajectories with Chronic Diseases: Evidence from Low Back Pain. 251-279 - Hyungyung Lee, Da Young Lee, Wonjae Kim, Jin-Hwa Kim, Tackeun Kim, Jihang Kim, Leonard Sunwoo, Edward Choi:
Vision-Language Generative Model for View-Specific Chest X-ray Generation. 280-296 - Marine Hoche, Olga Mineeva, Manuel Burger, Alessandro Blasimme, Gunnar Rätsch:
FAMEWS: a Fairness Auditing tool for Medical Early-Warning Systems. 297-311 - Qing En, Yuhong Guo:
Unsupervised Domain Adaptation for Medical Image Segmentation with Dynamic Prototype-based Contrastive Learning. 312-325 - Lorenzo Bini, Fatemeh Nassajian Mojarrad, Margarita Liarou, Thomas Matthes, Stéphane Marchand-Maillet:
FlowCyt: A Comparative Study of Deep Learning Approaches for Multi-Class Classification in Flow Cytometry Benchmarking. 326-338 - Stefan Hegselmann, Shannon Shen, Florian Gierse, Monica Agrawal, David A. Sontag, Xiaoyi Jiang:
A Data-Centric Approach To Generate Faithful and High Quality Patient Summaries with Large Language Models. 339-379 - 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:
Addressing Wearable Sleep Tracking Inequity: A New Dataset and Novel Methods for a Population with Sleep Disorders. 380-396 - Alireza Amirshahi, Jonathan Dan, Jose Angel Miranda, Amir Aminifar, David Atienza:
FETCH: A Fast and Efficient Technique for Channel Selection in EEG Wearable Systems. 397-409 - Ann-Kristin Balve, Peter Hendrix:
Interpretable breast cancer classification using CNNs on mammographic images. 410-426 - Wai Tak Lau, Ye Tian, Roshan Kenia, Saanvi Aima, Kaveri A. Thakoor:
Using Expert Gaze for Self-Supervised and Supervised Contrastive Learning of Glaucoma from OCT Data. 427-445 - Hamza Mahdi, Eptehal Nashnoush, Rami Saab, Arjun Balachandar, Rishit Dagli, Lucas X. Perri, Houman Khosravani:
Tuning In: Comparative Analysis of Audio Classifier Performance in Clinical Settings with Limited Data. 446-460 - Raghav Tandon, James J. Lah, Cassie S. Mitchell:
s-SuStaIn: Scaling subtype and stage inference via simultaneous clustering of subjects and biomarkers. 461-476 - Kevin Wu, Eric Wu, Kit T. Rodolfa, Daniel E. Ho, James Zou:
Regulating AI Adaptation: An Analysis of AI Medical Device Updates. 477-488 - Hiba Ahsan, Denis Jered McInerney, Jisoo Kim, Christopher Potter, Geoffrey S. Young, Silvio Amir, Byron C. Wallace:
Retrieving Evidence from EHRs with LLMs: Possibilities and Challenges. 489-505 - Nicolas Raymond, Hakima Laribi, Maxime Caru, Mehdi Mitiche, Valérie Marcil, Maja Krajinovic, Daniel Curnier, Daniel Sinnett, Martin Vallières:
Development of Error Passing Network for Optimizing the Prediction of VO2 peak in Childhood Acute Leukemia Survivors. 506-521 - Yubin Kim, Xuhai Xu, Daniel McDuff, Cynthia Breazeal, Hae Won Park:
Health-LLM: Large Language Models for Health Prediction via Wearable Sensor Data. 522-539 - Hugo Yèche, Manuel Burger, Dinara Veshchezerova, Gunnar Rätsch:
Dynamic Survival Analysis for Early Event Prediction. 540-557 - Mariia Sidulova, Seyed Kahaki, Ian S. Hagemann, Alexej Gossmann:
Contextual Unsupervised Deep Clustering in Digital Pathology. 558-565 - Antoine Nzeyimana, Anthony Campbell, James M. Scanlan, Joanne Stekler, Jenna L. Marquard, Barry Saver, Jeremy Gummeson:
DoseMate: A Real-world Evaluation of Machine Learning Classification of Pill Taking Using Wrist-worn Motion Sensors. 566-581 - Tamas Visy, Rita Kuznetsova, Christian Holz, Shkurta Gashi:
Systematic Evaluation of Self-Supervised Learning Approaches for Wearable-Based Fatigue Recognition. 582-596 - Aishwarya Mandyam, Matthew Jörke, William Denton, Barbara E. Engelhardt, Emma Brunskill:
Adaptive Interventions with User-Defined Goals for Health Behavior Change. 597-618 - Marika M. Cusick, Glenn M. Chertow, Douglas K. Owens, Michelle Y. Williams, Sherri Rose:
Algorithmic Changes Are Not Enough: Evaluating the Removal of Race Adjustment From the eGFR Equation. 619-643 - Patrick Kasl, Severine Soltani, Lauryn Keeler Bruce, Varun K. Viswanath, Wendy Hartogensis, Amarnath Gupta, Ilkay Altintas, Stephan Dilchert, Frederick M. Hecht, Ashley E. Mason, Benjamin L. Smarr:
A cross-study Analysis of Wearable Datasets and the Generalizability of Acute Illness Monitoring Models. 644-682 - Mukund Telukunta, Sukruth Rao, Gabriella Stickney, Venkata Sriram Siddhardh Nadendla, Casey Canfield:
Learning Social Fairness Preferences from Non-Expert Stakeholder Opinions in Kidney Placement. 683-695
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