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. © 2016 The Authors. Published by Elsevier Inc. on behalf of the Alzheimer’s Association. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Crowdsourced estimation of cognitive decline and resilience in Alzheimer's disease / Allen, Genevera I.; Amoroso, Nicola; Anghel, Catalina; Balagurusamy, Venkat; Bare, Christopher J.; Beaton, Derek; Bellotti, Roberto; Bennett, David A.; Boehme, Kevin L.; Boutros, Paul C.; Caberlotto, Laura; Caloian, Cristian; Campbell, Frederick; Chaibub Neto, Elias; Chang, Yu Chuan; Chen, Beibei; Chen, Chien Yu; Chien, Ting Ying; Clark, Tim; Das, Sudeshna; Davatzikos, Christos; Deng, Jieyao; Dillenberger, Donna; Dobson, Richard J. B.; Dong, Qilin; Doshi, Jimit; Duma, Denise; Errico, Rosangela; Erus, Guray; Everett, Evan; Fardo, David W.; Friend, Stephen H.; Fröhlich, Holger; Gan, Jessica; St George Hyslop, Peter; Ghosh, Satrajit S.; Glaab, Enrico; Green, Robert C.; Guan, Yuanfang; Hong, Ming Yi; Huang, Chao; Hwang, Jinseub; Ibrahim, Joseph; Inglese, Paolo; Iyappan, Anandhi; Jiang, Qijia; Katsumata, Yuriko; Kauwe, John S. K; Klein, Arno; Kong, Dehan; Krause, Roland; Lalonde, Emilie; Lauria, Mario; Lee, Eunjee; Lin, Xihui; Liu, Zhandong; Livingstone, Julie; Logsdon, Benjamin A.; Lovestone, Simon; Ma, Tsung Wei; Malhotra, Ashutosh; Mangravite, Lara M.; Maxwell, Taylor J.; Merrill, Emily; Nagorski, John; Namasivayam, Aishwarya; Narayan, Manjari; Naz, Mufassra; Newhouse, Stephen J.; Norman, Thea C.; Nurtdinov, Ramil N.; Oyang, Yen Jen; Pawitan, Yudi; Peng, Shengwen; Peters, Mette A.; Piccolo, Stephen R.; Praveen, Paurush; Priami, Corrado; Sabelnykova, Veronica Y.; Senger, Philipp; Shen, Xia; Simmons, Andrew; Sotiras, Aristeidis; Stolovitzky, Gustavo; Tangaro, Sabina; Tateo, Andrea; Tung, Yi An; Tustison, Nicholas J.; Varol, Erdem; Vradenburg, George; Weiner, Michael W.; Xiao, Guanghua; Xie, Lei; Xie, Yang; Xu, Jia; Yang, Hojin; Zhan, Xiaowei; Zhou, Yunyun; Zhu, Fan; Zhu, Hongtu; Zhu, Shanfeng. - In: ALZHEIMER'S & DEMENTIA. - ISSN 1552-5260. - 12:6(2016), pp. 645-653. [10.1016/j.jalz.2016.02.006]
Crowdsourced estimation of cognitive decline and resilience in Alzheimer's disease
Lauria, Mario;Priami, Corrado;
2016-01-01
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. © 2016 The Authors. Published by Elsevier Inc. on behalf of the Alzheimer’s Association. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).| File | Dimensione | Formato | |
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