- Main
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;
- Neto, Elias Chaibub;
- Chang, Yu‐Chuan;
- Chen, Beibei;
- Chen, Chien‐Yu;
- Chien, Ting‐Ying;
- Clark, Tim;
- Das, Sudeshna;
- Davatzikos, Christos;
- Deng, Jieyao;
- Dillenberger, Donna;
- Dobson, Richard JB;
- 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 SK;
- 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;
- Initiative, Alzheimer's Disease Neuroimaging
- et al.
Published Web Location
https://doi.org/10.1016/j.jalz.2016.02.006Abstract
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.
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