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Crowdsourced estimation of cognitive decline and resilience in Alzheimer's disease

 
: Allen, G.I.; Amoroso, N.; Anghel, C.; Balagurusamy, V.; Bare, C.J.; Beaton, D.; Bellotti, R.; Bennett, D.A.; Boehme, K.L.; Boutros, P.C.; Caberlotto, L.; Caloian, C.; Campbell, F.; Chaibub Neto, E.; Chang, Y.-C.; Chen, B.; Chen, C.-Y.; Chien, T.-Y.; Clark, T.; Das, S.; Davatzikos, C.; Deng, J.; Dillenberger, D.; Dobson, R.J.B.; Dong, Q.; Doshi, J.; Duma, D.; Errico, R.; Erus, G.; Everett, E.; Fardo, D.W.; Friend, S.H.; Fröhlich, H.; Gan, J.; St George-Hyslop, P.; Ghosh, S.S.; Glaab, E.; Green, R.C.; Guan, Y.; Hong, M.-Y.; Huang, C.; Hwang, J.; Ibrahim, J.; Inglese, P.; Iyappan, A.; Jiang, Q.; Katsumata, Y.; Kauwe, J.S.K.; Klein, A.; Kong, D.; Krause, R.; Lalonde, E.; Lauria, M.; Lee, E.; Lin, X.; Liu, Z.; Livingstone, J.; Logsdon, B.A.; Lovestone, S.; Ma, T.-W.; Malhotra, A.; Mangravite, L.M.; Maxwell, T.J.; Merrill, E.; Nagorski, J.; Namasivayam, A.; Narayan, M.; Naz, M.; Newhouse, S.J.; Norman, T.C.; Nurtdinov, R.N.; Oyang, Y.-J.; Pawitan, Y.; Peng, S.; Peters, M.A.; Piccolo, S.R.; Praveen, P.; Priami, C.; Sabelnykova, V.Y.; Senger, P.; Shen, X.; Simmons, A.; Sotiras, A.; Stolovitzky, G.; Tangaro, S.; Tateo, A.; Tung, Y.-A.; Tustison, N.J.; Varol, E.; Vradenburg, G.; Weiner, M.W.; Xiao, G.; Xie, L.; Xie, Y.; Xu, J.; Yang, H.; Zhan, X.; Zhou, Y.; Zhu, F.; Zhu, H.; Zhu, S.

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Alzheimer's & dementia 12 (2016), Nr.6, S.645-653
ISSN: 1552-5260
ISSN: 1552-5279
Englisch
Zeitschriftenaufsatz
Fraunhofer SCAI ()

Abstract
Identifying accurate biomarkers of cognitive decline is essential for advancing early diagnosis and prevention therapies in Alzheimer's disease. The Alzheimer's disease DREAM Challenge was designed as a computational crowdsourced project to benchmark the current state-of-the-art in predicting cognitive outcomes in Alzheimer's disease based on high dimensional, publicly available genetic and structural imaging data. This meta-analysis failed to identify a meaningful predictor developed from either data modality, suggesting that alternate approaches should be considered for prediction of cognitive performance.

: http://publica.fraunhofer.de/dokumente/N-421915.html