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1st ML4MHD 2023: Honolulu, Hawaii, USA
- Andreas K. Maier
, Julia A. Schnabel
Machine Learning for Multimodal Healthcare Data - First International Workshop, ML4MHD 2023, Honolulu, Hawaii, USA, July 29, 2023, Proceedings. Lecture Notes in Computer Science 14315, Springer 2024, ISBN 978-3-031-47678-5 - Frances M. Aponte-Caraballo
Death Prediction by Race in Colorectal Cancer Patients Using Machine Learning Approaches. 1-6 - Harsh Shrivastava, Urszula Chajewska:
Neural Graph Revealers. 7-25 - Tobias Weise
Multi-modal Biomarker Extraction Framework for Therapy Monitoring of Social Anxiety and Depression Using Audio and Video. 26-42 - Jeongwon Lee, Dae-Shik Kim:
RobustSsF: Robust Missing Modality Brain Tumor Segmentation with Self-supervised Learning-Based Scenario-Specific Fusion. 43-53 - Daisy Yi Ding, Xiaotao Shen
Semi-supervised Cooperative Learning for Multiomics Data Fusion. 54-63 - Yongsheng Mei
Exploiting Partial Common Information Microstructure for Multi-modal Brain Tumor Segmentation. 64-85 - Anastasiya Belyaeva, Justin Cosentino, Farhad Hormozdiari, Krish Eswaran, Shravya Shetty, Greg Corrado, Andrew Carroll, Cory Y. McLean, Nicholas A. Furlotte:
Multimodal LLMs for Health Grounded in Individual-Specific Data. 86-102 - Farnaz Khun Jush
Speed-of-Sound Mapping for Pulse-Echo Ultrasound Raw Data Using Linked-Autoencoders. 103-114 - Karthik Shetty, Annette Birkhold, Bernhard Egger, Srikrishna Jaganathan, Norbert Strobel, Markus Kowarschik, Andreas K. Maier:
HOOREX: Higher Order Optimizers for 3D Recovery from X-Ray Images. 115-124 - Debesh Jha, Vanshali Sharma, Neethi Dasu, Nikhil Kumar Tomar, Steven Hicks, Manas Kamal Bhuyan, Pradip K. Das, Michael A. Riegler, Pål Halvorsen, Ulas Bagci, Thomas de Lange
GastroVision: A Multi-class Endoscopy Image Dataset for Computer Aided Gastrointestinal Disease Detection. 125-140 - Niharika Shimona D'Souza, Hongzhi Wang, Andrea Giovannini, Antonio Foncubierta-Rodríguez, Kristen L. Beck, Orest B. Boyko, Tanveer F. Syeda-Mahmood:
MaxCorrMGNN: A Multi-graph Neural Network Framework for Generalized Multimodal Fusion of Medical Data for Outcome Prediction. 141-154 - Sunmin Eom
SIM-CNN: Self-supervised Individualized Multimodal Learning for Stress Prediction on Nurses Using Biosignals. 155-171 - Dominic Giles, Robert J. Gray, Chris Foulon, Guilherme Pombo, Tianbo Xu, James K. Ruffle
InterSynth: A Semi-Synthetic Framework for Benchmarking Prescriptive Inference from Observational Data. 172-188
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