E-bok, Engelska, 2021
Clinical Image-Based Procedures, Distributed and Collaborative Learning, Artificial Intelligence for Combating COVID-19 and Secure and Privacy-Preserving Machine Learning
Av Jonathan Passerat-Palmbach, Dmitrii Usynin, Alexander Ziller, Daniel Rueckert, Michal Guindy, Ender Konukoglu, Maria Gabrani, Daguang Xu, Xiaoxiao Li, Holger Roth, Nicola Rieke, Bennett Landman, Spyridon Bakas, Shadi Albarqouni, Yufei Chen, Klaus Drechsler, Marius Erdt, Stefan Wesarg, Raj Shekhar, Marius George Linguraru, Georgios Kaissis, Michal Rosen-Zvi, M. Jorge Cardoso, Cristina Oyarzun Laura
797 kr
Skickas måndag 12/10
Beskrivning
CLIP 2021 accepted 9 papers from the 13 submissions received. It focuses on holistic patient models for personalized healthcare with the goal to bring basic research methods closer to the clinical practice.
For DCL 2021, 4 papers from 7 submissions were accepted for publication. They deal with machine learning applied to problems where data cannot be stored in centralized databases and information privacy is a priority.
LL-COVID19 2021 accepted 2 papers out of 3 submissions dealing with the use of AI models in clinical practice.
And for PPML 2021, 2 papers were accepted from a total of 6 submissions, exploring the use of privacy techniques in the medical imaging community.
Produktinformation
- Utgivningsdatum: 2021-11-13
- Format: E-bok
- Språk: Engelska
- Förlag: Springer International Publishing
- ISBN: 9783030908744
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