Band 13596
Machine Learning in Clinical Neuroimaging 5th International Workshop, MLCN 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Proceedings
Aus der Reihe
Lecture Notes in Computer Science
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- Taschenbuch ausgewählt
- eBook
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Sprache:Englisch
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Auflage:1st edition 2022
Fr. 79.90
inkl. gesetzl. MwSt.,
Beschreibung
Produktdetails
Einband
Taschenbuch
Erscheinungsdatum
08.10.2022
Herausgeber
Ahmed Abdulkadir + weitereVerlag
SpringerSeitenzahl
180
Maße (L/B/H)
23.5/15.5/1.1 cm
Gewicht
300 g
Auflage
1st edition 2022
Sprache
Englisch
ISBN
978-3-031-17898-6
This book constitutes the refereed proceedings of the 5th International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2022, held in Conjunction with MICCAI 2022, Singapore in September 2022.
The book includes 17 papers which were carefully reviewed and selected from 23 full-length submissions.
The 5th international workshop on Machine Learning in Clinical Neuroimaging (MLCN2022) aims to bring together the top researchers in both machine learning and clinical neuroscience as well as tech-savvy clinicians to address two main challenges: 1) development of methodological approaches for analyzing complex and heterogeneous neuroimaging data (machine learning track); and 2) filling the translational gap in applying existing machine learning methods in clinical practices (clinical neuroimaging track).
The papers are categorzied into topical sub-headings: Morphometry; Diagnostics, and Aging, and Neurodegeneration.
The book includes 17 papers which were carefully reviewed and selected from 23 full-length submissions.
The 5th international workshop on Machine Learning in Clinical Neuroimaging (MLCN2022) aims to bring together the top researchers in both machine learning and clinical neuroscience as well as tech-savvy clinicians to address two main challenges: 1) development of methodological approaches for analyzing complex and heterogeneous neuroimaging data (machine learning track); and 2) filling the translational gap in applying existing machine learning methods in clinical practices (clinical neuroimaging track).
The papers are categorzied into topical sub-headings: Morphometry; Diagnostics, and Aging, and Neurodegeneration.
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