Interpretability of Machine Intelligence in Medical Image Computing and Multimodal Learning for Clinical Decision Support a book to read published by Springer Nature on 2019-10-24 is very good to you if you search book about Computers / Intelligence (AI) & Semantics, Mathematics / Logic, Medical / General, Computers / Computer Graphics, Computers / Information Technology, Mathematics / Discrete Mathematics, Computers / Social Aspects, Computers / Optical Data Processing, . a book to read writed by Kenji Suzuki, Mauricio Reyes, Tanveer Syeda-Mahmood, Ender Konukoglu, Ben Glocker, Roland Wiest, Yaniv Gur, Hayit Greenspan, Anant Madabhushi, with page count 93 Pages. You can read book summary bellow
Download Interpretability of Machine Intelligence in Medical Image Computing and Multimodal Learning for Clinical Decision Support Second International Workshop, iMIMIC 2019, and 9th International Workshop, ML-CDS 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings all pages
ISBN: 9783030338503
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.
Interpretability of Machine Intelligence in Medical Image Computing and Multimodal Learning for Clinical Decision Support
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