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Titel:

Multi-modal Disease Classification in Incomplete Datasets Using Geometric Matrix Completion.

Dokumenttyp:
Konferenzbeitrag
Autor(en):
Vivar, G.; Zwergal, A.; Navab, N.; Ahmadi, A.
Abstract:
In large population-based studies and in clinical routine, tasks like disease diagnosis and progression prediction are inherently based on a rich set of multi-modal data, including imaging and other sensor data, clinical scores, phenotypes, labels and demographics. However, missing features, rater bias and inaccurate measurements are typical ailments of real-life medical datasets. Recently, it has been shown that deep learning with graph convolution neural networks (GCN) can outperform tradition...     »
Stichworte:
MICCAI-GRAIL,GeometricMatrixCompletion,classification,deeplearning
Herausgeber:
Stoyanov, Danail; Taylor, Zeike; Ferrante, Enzo; Dalca, Adrian V.; Martel, Anne; Maier-Hein, Lena; Parisot, Sarah; Sotiras, Aristeidis; Papiez, Bartlomiej; Sabuncu, Mert R.; Shen, Li
Kongress- / Buchtitel:
Graphs in Biomedical Image Analysis and Integrating Medical Imaging and Non-Imaging Modalities
Verlag / Institution:
Springer International Publishing
Verlagsort:
Cham
Jahr:
2018
Seiten:
24--31
Print-ISBN:
978-3-030-00689-1
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