TY - BOOK
T1 - Interpretability of Machine Intelligence in Medical Image Computing and Multimodal Learning for Clinical Decision Support
T2 - Second International Workshop, iMIMIC 2019, and 9th International Workshop, ML-CDS 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings
A2 - Suzuki, Kenji
A2 - Reyes, Mauricio
A2 - Syeda-Mahmood, Tanveer
A2 - Konukoglu, Ender
A2 - Glocker, Ben
A2 - Wiest, Roland
A2 - Gur, Yaniv
A2 - Greenspan, Hayit
A2 - Madabhushi, Anant
N1 - Includes index.
PY - 2019
Y1 - 2019
N2 - This book constitutes the refereed joint proceedings of the Second International Workshop on Interpretability of Machine Intelligence in Medical Image Computing, iMIMIC 2019, and the 9th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2019, held in conjunction with the 22nd International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2019, in Shenzhen, China, in October 2019. The 7 full papers presented at iMIMIC 2019 and the 3 full papers presented at ML-CDS 2019 were carefully reviewed and selected from 10 submissions to iMIMIC and numerous submissions to ML-CDS. The iMIMIC papers focus on introducing the challenges and opportunities related to the topic of interpretability of machine learning systems in the context of medical imaging and computer assisted intervention. The ML-CDS papers discuss machine learning on multimodal data sets for clinical decision support and treatment planning. .
AB - This book constitutes the refereed joint proceedings of the Second International Workshop on Interpretability of Machine Intelligence in Medical Image Computing, iMIMIC 2019, and the 9th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2019, held in conjunction with the 22nd International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2019, in Shenzhen, China, in October 2019. The 7 full papers presented at iMIMIC 2019 and the 3 full papers presented at ML-CDS 2019 were carefully reviewed and selected from 10 submissions to iMIMIC and numerous submissions to ML-CDS. The iMIMIC papers focus on introducing the challenges and opportunities related to the topic of interpretability of machine learning systems in the context of medical imaging and computer assisted intervention. The ML-CDS papers discuss machine learning on multimodal data sets for clinical decision support and treatment planning. .
U2 - 10.1007/978-3-030-33850-3
DO - 10.1007/978-3-030-33850-3
M3 - ???researchoutput.researchoutputtypes.bookanthology.book???
SN - 978-3-030-33849-7
T3 - Image Processing, Computer Vision, Pattern Recognition, and Graphics
BT - Interpretability of Machine Intelligence in Medical Image Computing and Multimodal Learning for Clinical Decision Support
PB - Springer International Publishing; Imprint: Springer
CY - Cham
ER -
