Multimodal Biomedical Data Fusion Using Sparse Canonical Correlation Analysis and Cooperative Learning: A Cohort Study on COVID-19

Through technological innovations, patient cohorts can be examined from multiple views with high-dimensional, multiscale biomedical data to classify clinical phenotypes and predict outcomes. Here, we aim to present our approach for analyzing multimodal data using unsupervised and supervised sparse l...

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Detalles Bibliográficos
Autores principales: Er, Ahmet Gorkem, Ding, Daisy Yi, Er, Berrin, Uzun, Mertcan, Cakmak, Mehmet, Sadée, Christoph, Durhan, Gamze, Ozmen, Mustafa Nasuh, Tanriover, Mine Durusu, Topeli, Arzu, Son, Yesim Aydin, Tibshirani, Robert, Unal, Serhat, Gevaert, Olivier
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Journal Experts 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10690316/
https://www.ncbi.nlm.nih.gov/pubmed/38045288
http://dx.doi.org/10.21203/rs.3.rs-3569833/v1

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10690316/
https://www.ncbi.nlm.nih.gov/pubmed/38045288
http://dx.doi.org/10.21203/rs.3.rs-3569833/v1

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