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ORCIDML4H@NeurIPS 2024: Vancouver, Canada
- Stefan Hegselmann, Helen Zhou, Elizabeth Healey, Trenton Chang, Caleb Ellington, Vishwali Mhasawade, Sana Tonekaboni, Peniel Argaw, Haoran Zhang:
Machine Learning for Health, ML4H@NeurIPS 2024, Vancouver, Canada, 15-16 December 2024. Proceedings of Machine Learning Research 259, PMLR 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 N. Argaw, Haoran Zhang:
Machine Learning for Health (ML4H) 2024. 1-13 - Isaac S. Kohane:
The Human Values Project. 14-18 - Matthew McDermott:
The (lack of?) Science of Machine Learning for Healthcare. 19-29 - Sarwan Ali, Prakash Chourasia, Haris Mansoor, Bipin Koirala, Murray Patterson:
MIK: Modified Isolation Kernel for Biological Sequence Visualization, Classification, and Clustering. 30-47 - Asfandyar Azhar:
The Self-Supervision Regime and Encoder Fit for Histopathology Image Analysis. 48-60 - Asfandyar Azhar, Amulyal Mathur, Sahil Jain, James Emilian, Shaurjya Mandal, Nidhish Shah, Yongjie Jessica Zhang:
Modeling Clinical Decision Variability in Explainable Multimodal Seizure Detection. 61-72 - Zarif L. Azher, Gokul Srinivasan, Keluo Yao, Minh-Khang Le, Ken Lau, Harsimran Kaur, Fred Kolling, Louis J. Vaickus, Xiaoying Lu, Joshua J. Levy:
Mapping Three-Dimensional Tumor Heterogeneity through Deep Learning Inference of Spatial Transcriptomics from Routine Histopathology: A Proof-of-Concept Comparative Study. 73-85 - Dominik Becker, Anita Just, Günter Hahn, Peter Herrmann, Leif Saager, Fabian H. Sinz:
RESIST: Remapping EIT Signals Using Implicit Spatially-Aware Transformer. 86-103 - David R. Bellamy, Bhawesh Kumar, Cindy Wang, Andrew Beam:
Labrador: Exploring the limits of masked language modeling for laboratory data. 104-129 - Teya S. Bergamaschi, Collin M. Stultz, Ridwan Alam:
Continuity Contrastive Representations of ECG for Heart Block Detection from Only Lead-I. 130-142 - 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:
MLV2-Net: Rater-Based Majority-Label Voting for Consistent Meningeal Lymphatic Vessel Segmentation. 143-153 - Ljubomir 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:
Development of Machine Learning Classifiers for Blood-based Diagnosis and Prognosis of Suspected Acute Infections and Sepsis. 154-170 - Xu Cao, Wenqian Ye, Kenny Moise, Megan Coffee:
MpoxVLM: A Vision-Language Model for Diagnosing Skin Lesions from Mpox Virus Infection. 171-185 - Jonathan F. Carter, Lionel Tarassenko:
wav2sleep: A Unified Multi-Modal Approach to Sleep Stage Classification from Physiological Signals. 186-202 - Jiaee Cheong, Aditya Bangar, Sinan Kalkan, Hatice Gunes:
U-Fair: Uncertainty-based Multimodal Multitask Learning for Fairer Depression Detection. 203-218 - Shih-Han Chou, Miini Teng, Harshinee Sriram, Chuyuan Li, Giuseppe Carenini, Cristina Conati, Thalia Shoshana Field, Hyeju Jang, Gabriel Murray:
Multimodal Classification of Alzheimer's Disease by Combining Facial and Eye-Tracking Data. 219-232 - Charles B. Delahunt, Courosh Mehanian, Matthew P. Horning:
Reducing Poisson error can offset classification error: a technique to meet clinical performance requirements. 233-247 - Leon Deng, Hong Xiong, Feng Wu, Sanyam Kapoor, Soumya Gosh, Zach Shahn, Li-Wei H. Lehman:
Uncertainty Quantification for Conditional Treatment Effect Estimation under Dynamic Treatment Regimes. 248-266 - Yella Diekmann, Chase Fensore, Rodrigo M. Carrillo-Larco, Nishant Pradhan, Bhavya Appana, Joyce C. Ho:
Evaluating Safety of Large Language Models for Patient-facing Medical Question Answering. 267-290 - Adibvafa Fallahpour, Mahshid Alinoori, Wenqian Ye, Xu Cao, Arash Afkanpour, Amrit Krishnan:
EHRMamba: Towards Generalizable and Scalable Foundation Models for Electronic Health Records. 291-307 - Hamed Fayyaz, Mehak Gupta, Alejandra Perez Ramirez, Claudine Jurkovitz, H. Timothy Bunnell, Thao-Ly T. Phan, Rahmatollah Beheshti:
An Interoperable Machine Learning Pipeline for Pediatric Obesity Risk Estimation. 308-324 - Johannes O. Ferstad, Emily B. Fox, David Scheinker, Ramesh Johari:
Learning Explainable Treatment Policies with Clinician-Informed Representations: A Practical Approach. 325-349 - Thomas Frost, Kezhi Li, Steve Harris:
Robust Real-Time Mortality Prediction in the Intensive Care Unit using Temporal Difference Learning. 350-363 - Ya Gao, Hans Moen, Saila Koivusalo, Miika Koskinen, Pekka Marttinen:
Query-Guided Self-Supervised Summarization of Nursing Notes. 364-383 - Maxence Gélard, Guillaume Richard, Thomas Pierrot, Paul-Henry Cournède:
BulkRNABert: Cancer prognosis from bulk RNA-seq based language models. 384-400 - Xiao Gu, Yu Liu, Zaineb Mohsin, Jonathan Bedford, Anshul Thakur, Peter J. Watkinson, Lei A. Clifton, Tingting Zhu, David A. Clifton:
Are Time Series Foundation Models Ready for Vital Sign Forecasting in Healthcare? 401-419 - Ariel Guerra-Adames, Marta Avalos Fernandez, Oceane Doremus, Cédric Gil-Jardiné, Emmanuel Lagarde:
Uncovering Judgment Biases in Emergency Triage: A Public Health Approach Based on Large Language Models. 420-439 - Arushi Gupta, Rafal Kocielnik, Jiayun Wang, Firdavs Nasriddinov, Cherine Yang, Elyssa Y. Wong, Anima Anandkumar, Andrew J. Hung:
Multi-Modal Self-Supervised Learning for Surgical Feedback Effectiveness Assessment. 440-455 - Kevin He, David Adam, Sarah Han-Oh, Anqi Liu:
Training-Aware Risk Control for Intensity Modulated Radiation Therapies Quality Assurance with Conformal Prediction. 456-470 - Sarah M. Hooper, Hui Xue:
A Study on Context Length and Efficient Transformers for Biomedical Image Analysis. 471-489 - Quanqi Hu, Ashok Vardhan Addala, Masaki Ikuta, Ravi Soni, Gopal Avinash:
Enhancing 3D Cardiac CT Segmentation with Latent Diffusion Model and Self-Supervised Learning. 490-501 - Haoxu Huang, Cem M. Deniz, Kyunghyun Cho, Sumit Chopra, Divyam Madaan:
HIST-AID: Leveraging Historical Patient Reports for Enhanced Multi-Modal Automatic Diagnosis. 502-523 - Muhammad Abdullah Jamal, Omid Mohareri:
Rethinking RGB-D Fusion for Semantic Segmentation in Surgical Datasets. 524-534 - Sooyong Jang, Kuk Jin Jang, Hyonyoung Choi, Yong-Seop Han, Seongjin Lee, Jin-hyun Kim, Insup Lee:
Fundus Image-based Visual Acuity Assessment with PAC-Guarantees. 535-549 - Eirini Kateri, Katayoun Farrahi:
ST2S-rPPG: A Spatiotemporal Two-Stage Learning Approach for Pulse Estimation Using Video. 550-562 - Shiva Kaul, Geoffrey J. Gordon:
Meta-Analysis with Untrusted Data. 563-593 - Vladislav Kim, Lisa Schneider, Soodeh Kalaie, Declan O'Regan, Christian Bender:
HeartMAE: Advancing Cardiac MRI Analysis through Optical Flow Guided Masked Autoencoding. 594-609 - Mahesh Babu Kommalapati, Xiao Gu, Harshit Pandey, Christie Rizzo, Charlene Collibee, Silvio Amir, Aarti Sathyanarayana:
Towards Preventing Intimate Partner Violence by Detecting Disagreements in SMS Communications. 610-622 - Pranav Kulkarni, Adway U. Kanhere, Paul H. Yi, Vishwa S. Parekh:
From Isolation to Collaboration: Federated Class-Heterogeneous Learning for Chest X-Ray Classification. 623-635 - Yahan Li, Keith Harrigian, Ayah Zirikly, Mark Dredze:
Are Clinical T5 Models Better for Clinical Text? 636-667 - Mingzhu Liu, Angela H. Chen, George H. Chen:
Generalized Prompt Tuning: Adapting Frozen Univariate Time Series Foundation Models for Multivariate Healthcare Time Series. 668-679 - Daniel Lopez-Martinez, Abhishek Bafna:
Detecting sensitive medical responses in general purpose large language models. 680-695 - Alessandro Marchese, Hans de Ferrante, Jeroen Berrevoets, Sam Verboven:
DynamITE: Optimal time-sensitive organ offers using ITE. 696-713 - Anton Matsson, Lena Stempfle, Yaochen Rao, Zachary R. Margolin, Heather J. Litman, Fredrik D. Johansson:
How Should We Represent History in Interpretable Models of Clinical Policies? 714-734 - Awais Naeem, Tianhao Li, Huang-Ru Liao, Jiawei Xu, Aby M. Mathew, Zehao Zhu, Zhen Tan, Ajay Kumar Jaiswal, Raffi A. Salibian, Ziniu Hu, Tianlong Chen, Ying Ding:
Path-RAG: Knowledge-Guided Key Region Retrieval for Open-ended Pathology Visual Question Answering. 735-746 - Pirouz Naghavi, Erica Naghavi, Gang Wang, Kanyin Liane Ong:
Self-Supervised Probability Imputation to Estimate the External-Natural Cause of Injury Matrix. 747-774 - Makiya Nakashima, Po-Hao Chen, Michael Bolen, Christopher Nguyen, W. H. Wilson Tang, Richard Grimm, Deborah Kwon, David Chen:
Indication Driven Autoregressive Report Generation for Cardiac Magnetic Resonance Imaging. 775-786 - Firdavs Nasriddinov, Rafal Kocielnik, Arushi Gupta, Cherine Yang, Elyssa Y. Wong, Anima Anandkumar, Andrew J. Hung:
Automating Feedback Analysis in Surgical Training: Detection, Categorization, and Assessment. 787-804 - Mike Van Ness, Billy Block, Madeleine Udell:
DNAMite: Interpretable Calibrated Survival Analysis with Discretized Additive Models. 805-823 - Brighton Nuwagira, Caner Korkmaz, Philmore Koung, Baris Coskunuzer:
Topological Machine Learning for Low Data Medical Imaging. 824-838 - Alain Ryser, Chuhao Feng, Tobias Scheithauer, Marc Pfister, Marie-Anne Burckhardt, Sara Bachmann, Alexander Marx, Julia E. Vogt:
Transfer Learning for Pediatric Glucose Forecasting. 839-860 - Krishnakant V. Saboo, Yurui Cao, Václav Kremen, Suguna Pappu, Philippa J. Karoly, Dean R. Freestone, Mark J. Cook, Gregory A. Worrell, Ravishankar K. Iyer:
State space modeling of multidien cyclical progression of epilepsy. 861-885 - Mozhgan Saeidi:
Streamlining Clinical Trial Recruitment: A Two-Stage Zero-Shot LLM Approach with Advanced Prompting. 886-896 - Elliot Schumacher, Daniel Rosenthal, Dhruv Naik, Varun Nair, Luladay Price, Geoffrey J. Tso, Anitha Kannan:
MED-OMIT: Extrinsically-Focused Evaluation Metric for Omissions in Medical Summarization. 897-922 - Shiv Shankar, Ritwik Sinha, Madalina Fiterau:
Estimating Counterfactual Distributions under Interference. 923-940 - 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 L. Hyland, Javier Alvarez-Valle:
MAIRA-Seg: Enhancing Radiology Report Generation with Segmentation-Aware Multimodal Large Language Models. 941-960 - Vipul Kumar Singh, Jyotismita Barman, Sandeep Kumar, Jayadeva:
CoRE-BOLD: Cross-Domain Robust and Equitable Ensemble for BOLD Signal Analysis. 961-975 - Ayush Singla, Shakson Isaac, Chirag J. Patel:
Barttender: An approachable & interpretable way to compare medical imaging and non-imaging data. 976-990 - Michael Vollenweider, Manuel Schürch, Chiara Rohrer, Gabriele Gut, Michael Krauthammer, Andreas Wicki:
Learning Personalized Treatment Decisions in Precision Medicine: Disentangling Treatment Assignment Bias in Counterfactual Outcome Prediction and Biomarker Identification. 991-1013 - John Wu, David Wu, Jimeng Sun:
DILA: Dictionary Label Attention for Mechanistic Interpretability in High-dimensional Multi-label Medical Coding Prediction. 1014-1038 - Jenny Xu:
Uncertainty Estimation in Large Vision Language Models for Automated Radiology Report Generation. 1039-1052 - Yuwei Zhang, Tong Xia, Aaqib Saeed, Cecilia Mascolo:
RespLLM: Unifying Audio and Text with Multimodal LLMs for Generalized Respiratory Health Prediction. 1053-1066 - Yuwei Zhang, Tong Xia, Abhirup Ghosh, Cecilia Mascolo:
Uncertainty-Aware Personalized Federated Learning for Realistic Healthcare Applications. 1067-1086 - Serena Zhang, Sraavya Sambara, Oishi Banerjee, Julián Nicolás Acosta, L. John Fahrner, Pranav Rajpurkar:
RadFlag: A Black-Box Hallucination Detection Method for Medical Vision Language Models. 1087-1103 - Rui Zhu, Jennifer Yu, Stephen H. Friend, Sarah M. Goodday, Bo Wang, Anna Goldenberg:
Towards a personalized pregnancy experience: Forecasting symptoms using graph neural networks and digital health technologies. 1104-1120
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last updated on 2025-08-28 01:01 CEST by the dblp team
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