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ORCIDMLHC 2024: Toronto, Canada
- Kaivalya Deshpande, Madalina Fiterau, Shalmali Joshi, Zachary C. Lipton, Rajesh Ranganath, Iñigo Urteaga:
Machine Learning for Healthcare Conference, 16-17 August 2024, Toronto, Canada. Proceedings of Machine Learning Research 252, PMLR 2024 - Haoran Zhang, Supriya Nagesh, Milind Shyani, Nina Mishra:
DOSSIER: Fact Checking in Electronic Health Records while Preserving Patient Privacy. - Hye Sun Yun, David Pogrebitskiy, Iain James Marshall, Byron C. Wallace:
Automatically Extracting Numerical Results from Randomized Controlled Trials with Large Language Models. - Hong Xiong, Feng Wu, Leon Deng, Megan Su, Li-Wei H. Lehman:
G-Transformer: Counterfactual Outcome Prediction under Dynamic and Time-varying Treatment Regimes. - Yuqing Wang, Malvika Pillai, Yun Zhao, Catherine M. Curtin, Tina Hernandez-Boussard:
FairEHR-CLP: Towards Fairness-Aware Clinical Predictions with Contrastive Learning in Multimodal Electronic Health Records. - Cécile Trottet, Manuel Schürch, Ahmed Allam, Imon Barua, Liubov Petelytska, Oliver Distler, Anna-Maria Hoffmann-Vold, Michael Krauthammer:
Semi-Supervised Generative Models for Disease Trajectories: A Case Study on Systemic Sclerosis. - Fatemeh Tavakoli, David B. Emerson, Sana Ayromlou, John Taylor Jewell, Amrit Krishnan, Yuchong Zhang, Amol Verma, Fahad Razak:
A Comprehensive View of Personalized Federated Learning on Heterogeneous Clinical Datasets. - Michael Staniek, Marius Fracarolli, Michael Hagmann, Stefan Riezler:
Early Prediction of Causes (not Effects) in Healthcare by Long-Term Clinical Time Series Forecasting. - Ziyang Song, Qincheng Lu, He Zhu, David L. Buckeridge, Yue Li:
Bidirectional Generative Pre-training for Improving Healthcare Time-series Representation Learning. - Baoyi Shi, Ying Liu, Shanghong Xie, Xi Zhu, Yuanjia Wang:
Network-Assisted Mediation Analysis with High-Dimensional Neuroimaging Mediators. - Judy Hanwen Shen, Inioluwa Deborah Raji, Irene Y. Chen:
The Data Addition Dilemma. - Abhishek Sharma, Sonali Parbhoo, Omer Gottesman, Finale Doshi-Velez:
Decision-Focused Model-based Reinforcement Learning for Reward Transfer. - Jacob Schultz, Jerry L. Prince, Bruno M. Jedynak:
Predictive Powered Inference for Healthcare; Relating Optical Coherence Tomography Scans to Multiple Sclerosis Disease Progression. - Saige Rutherford, Thomas Wolfers, Charlotte J. Fraza, Nathaniel G. Harnett, Christian F. Beckmann, Henricus G. Ruhe, Andre F. Marquand:
To which reference class do you belong? Measuring racial fairness of reference classes with normative modeling. - Umaima Rahman, Abhishek Basu, Muhammad Uzair Khattak, Aniq Ur Rahman:
XDT-CXR: Investigating Cross-Disease Transferability in Zero-Shot Binary Classification of Chest X-Rays. - Nassim Oufattole, Hyewon Jeong, Matthew B. A. McDermott
, Aparna Balagopalan, Bryan Jangeesingh, Marzyeh Ghassemi, Collin M. Stultz:
Event-Based Contrastive Learning for Medical Time Series. - Mikkel Odgaard, Kiril Vadimovic Klein, Martin Sillesen, Sanne Møller Thysen, Espen Jimenez-Solem, Mads Nielsen:
CORE-BEHRT: A Carefully Optimized and Rigorously Evaluated BEHRT. - Jamie Norris, Aswin Chari, Dorien van Blooijs, Gerald K. Cooray, Karl J. Friston, Martin Tisdall, Richard Rosch:
Localising the Seizure Onset Zone from Single-Pulse Electrical Stimulation Responses with a CNN Transformer. - Sujay Nagaraj, Andrew J. Goodwin, Dmytro Lopushanskyy, Sebastian D. Goodfellow, Danny Eytan, Hadrian Balaci, Robert Greer, Anand Jayarajan, Azadeh Assadi, Mjaye Leslie Mazwi, Anna Goldenberg:
Needles in Needle Stacks: Meaningful Clinical Information Buried in Noisy Sensor Data. - Yun Chao Lin, Andrea Clark-Sevilla, Rohith Ravindranath, Fthimnir Hassan, Justin Reyes, Joseph Lombardi, Lawrence G. Lenke, Ansaf Salleb-Aouissi:
A LUPI distillation-based approach: Application to predicting Proximal Junctional Kyphosis. - Bhawesh Kumar, Jonathan Amar, Eric Yang, Nan Li, Yugang Jia:
Selective Fine-tuning on LLM-labeled Data May Reduce Reliance on Human Annotation: A Case Study Using Schedule-of-Event Table Detection. - Woojung Kim, Paul A. Jenkins, Christopher Yau:
Mixed Type Multimorbidity Variational Autoencoder: A Deep Generative Model for Multimorbidity Analysis. - Junu Kim, Chaeeun Shim, Bosco Seong Kyu Yang, Chami Im, Sung Yoon Lim, Han-Gil Jeong, Edward Choi:
General-Purpose Retrieval-Enhanced Medical Prediction Model Using Near-Infinite History. - Abhishek Jaiswal, Nisheeth Srivastava:
Benchmarking Reliability of Deep Learning Models for Pathological Gait Classification. - Alyssa Huang, Oishi Banerjee, Kay Wu, Eduardo Pontes Reis, Pranav Rajpurkar:
FineRadScore: A Radiology Report Line-by-Line Evaluation Technique Generating Corrections with Severity Scores. - Yijie Hao, Huan He, Joyce C. Ho:
LLMSYN: Generating Synthetic Electronic Health Records Without Patient-Level Data. - Juan Jose Garcia, Nikhil Sarin, Rebecca Kitzmiller, Ashok K. Krishnamurthy, Jessica K. Zègre-Hemsey:
Risk stratification through class-conditional conformal estimation: A strategy that improves the rule-out performance of MACE in the prehospital setting. - Xiang Gao, Michael Cooper, Maryam Naghibzadeh, Amirhossein Azhie, Mamatha Bhat, Rahul G. Krishnan:
Predicting Long-Term Allograft Survival in Liver Transplant Recipients. - Vaibhav Ganatra, Drishti Goel:
PRECISe : Prototype-Reservation for Explainable classification under Imbalanced and Scarce-Data Settings. - Lucia Filippozzi, Santiago Mazuelas, Iñigo Urteaga:
Minimax Risk Classifiers for Mislabeled Data: a Study on Patient Outcome Prediction Tasks. - Hamed Fayyaz, Niharika S. D'Souza, Rahmatollah Beheshti:
Multimodal Sleep Apnea Detection with Missing or Noisy Modalities. - Hylke C. Donker, Dorien Neijzen, Johann de Jong, Gerton A. Lunter:
Multinomial belief networks for healthcare data. - Rishit Dagli, Atsuhiro Hibi, Rahul G. Krishnan, Pascal N. Tyrrell:
NeRF-US: Removing Ultrasound Imaging Artifacts from Neural Radiance Fields in the Wild. - Jihye Choi, Nils Palumbo, Prasad Chalasani, Matthew M. Engelhard, Somesh Jha, Anivarya Kumar, David Page:
MALADE: Orchestration of LLM-powered Agents with Retrieval Augmented Generation for Pharmacovigilance. - Isabel Chien, Cliff Wong, Zelalem Gero, Jaspreet Bagga, Risa Ueno, Richard E. Turner, Roshanthi Weerasinghe, Brian Piening, Tristan Naumann, Carlo Bifulco, Hoifung Poon, Javier González Hernández:
Beyond Clinical Trials: Using Real World Evidence to Investigate Heterogeneous, Time-Varying Treatment Effects. - Nimeesha Chan, Felix Parker, William Bennett, Tianyi Wu, Mung Yao Jia, James Fackler, Kimia Ghobadi:
Leveraging LLMs for Multimodal Medical Time Series Analysis. - Oishi Banerjee, Hong-Yu Zhou, Kay Wu, Subathra Adithan, Stephen Kwak, Pranav Rajpurkar:
Direct Preference Optimization for Suppressing Hallucinated Prior Exams in Radiology Report Generation. - Arnold Caleb Asiimwe, Didac Suris Coll-Vinent, Pranav Rajpurkar, Carl Vondrick:
MedAutoCorrect: Image-Conditioned Autocorrection in Medical Reporting.
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