Machine Learning in Clinical Neuroimaging and Radiogenomics in Neuro-oncology / Lecture Notes in Computer Science Bd.12449 (PDF)
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For MLCN 2020, 18 papers out of 28 submissions were accepted for publication. The accepted papers present novel contributions in both developing new machine learning methods and applications of existing methods to solve challenging problems in clinical neuroimaging.
For RNO-AI 2020, all 8 submissions were accepted for publication. They focus on addressing the problems of applying machine learning to large and multi-site clinical neuroimaging datasets. The workshop aimed to bring together experts in both machine learning and clinical neuroimaging to discuss and hopefully bridge the existing challenges of applied machine learning in clinical neuroscience.
*The workshops were held virtually due to the COVID-19 pandemic.
- 2020, 1st ed. 2020, 305 Seiten, Englisch
- Herausgegeben: Seyed Mostafa Kia, Saima Rathore, Madhura Ingalhalikar, Hassan Mohy-ud-Din, Ahmed Abdulkadir, Cher Bass, Mohamad Habes, Jane Maryam Rondina, Chantal Tax, Hongzhi Wang, Thomas Wolfers
- Verlag: Springer International Publishing
- ISBN-10: 3030668436
- ISBN-13: 9783030668433
- Erscheinungsdatum: 30.12.2020
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- Größe: 50 MB
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