TY - BOOK
T1 - Multimodal Learning for Clinical Decision Support and Clinical Image-Based Procedures
T2 - 10th International Workshop, ML-CDS 2020, and 9th International Workshop, CLIP 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4–8, 2020, Proceedings
A2 - Drechsler, Klaus
A2 - Erdt, Marius
A2 - González Ballester, Miguel Ángel
A2 - Greenspan, Hayit
A2 - Karargyris, Alexandros
A2 - Linguraru, Marius George
A2 - Madabhushi, Anant
A2 - Oyarzun Laura, Cristina
A2 - Shekhar, Raj
A2 - Syeda-Mahmood, Tanveer
A2 - Wesarg, Stefan
N1 - Springer eBooks
PY - 2020
Y1 - 2020
N2 - This book constitutes the refereed joint proceedings of the 10th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2020, and the 9th International Workshop on Clinical Image-Based Procedures, CLIP 2020, held in conjunction with the 23rd International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2020, in Lima, Peru, in October 2020. The workshops were held virtually due to the COVID-19 pandemic. The 4 full papers presented at ML-CDS 2020 and the 9 full papers presented at CLIP 2020 were carefully reviewed and selected from numerous submissions to ML-CDS and 10 submissions to CLIP. The ML-CDS papers discuss machine learning on multimodal data sets for clinical decision support and treatment planning. The CLIP workshops provides a forum for work centered on specific clinical applications, including techniques and procedures based on comprehensive clinical image and other data.
AB - This book constitutes the refereed joint proceedings of the 10th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2020, and the 9th International Workshop on Clinical Image-Based Procedures, CLIP 2020, held in conjunction with the 23rd International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2020, in Lima, Peru, in October 2020. The workshops were held virtually due to the COVID-19 pandemic. The 4 full papers presented at ML-CDS 2020 and the 9 full papers presented at CLIP 2020 were carefully reviewed and selected from numerous submissions to ML-CDS and 10 submissions to CLIP. The ML-CDS papers discuss machine learning on multimodal data sets for clinical decision support and treatment planning. The CLIP workshops provides a forum for work centered on specific clinical applications, including techniques and procedures based on comprehensive clinical image and other data.
U2 - 10.1007/978-3-030-60946-7
DO - 10.1007/978-3-030-60946-7
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T3 - Image Processing, Computer Vision, Pattern Recognition, and Graphics
BT - Multimodal Learning for Clinical Decision Support and Clinical Image-Based Procedures
PB - Springer International Publishing; Imprint: Springer
CY - Cham
ER -
