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Document type:
Konferenzbeitrag 
Author(s):
Kazi, A.; Krishna, S.; Shekarforoush, S.; Kortü m, K.; Albarqouni, S.; Navab, N. 
Title:
Self-Attention Equipped Graph Convolutions for Disease Prediction (Oral) 
Abstract:
Multi-modal data comprising imaging (MRI, fMRI, PET, etc.) and non-imaging (clinical test, demographics, etc.) data can be collected together and used for disease prediction. Such diverse data gives complementary information about the patientÅ› condition to make an informed diagnosis. A model capable of leveraging the individuality of each multi-modal data is required for better disease prediction. We propose a graph convolution based deep model which takes into account the distinctiveness of ea...    »
 
Keywords:
isbi,camp 
Book / Congress title:
2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019) 
Organization:
Ieee 
Year:
2019 
Pages:
1896--1899