Allen, Genevera I.Amoroso, NicolaAnghel, CatalinaBalagurusamy, VenkatBare, Christopher J.Beaton, DerekBellotti, RobertoBennett, David A.Boehme, Kevin L.Boutros, Paul C.Caberlotto, LauraCaloian, CristianCampbell, FrederickNeto, Elias ChaibubChang, Yu-ChuanChen, BeibeiChen, Chien-YuChien, Ting-YingClark, TimDas, SudeshnaDavatzikos, ChristosDeng, JieyaoDillenberger, DonnaDobson, Richard J.B.Dong, QilinDoshi, JimitDuma, DeniseErrico, RosangelaErus, GurayEverett, EvanFardo, David W.Friend, Stephen H.Frӧhlich, HolgerGan, JessicaSt George-Hyslop, PeterGhosh, Satrajit S.Glaab, EnricoGreen, Robert C.Guan, YuanfangHong, Ming-YiHuang, ChaoHwang, JinseubIbrahim, JosephInglese, PaoloIyappan, AnandhiJiang, QijiaKatsumata, YurikoKauwe, John S.K.Klein, ArnoKong, DehanKrause, RolandLalonde, EmilieLauria, MarioLee, EunjeeLin, XihuiLiu, ZhandongLivingstone, JulieLogsdon, Benjamin A.Lovestone, SimonMa, Tsung-weiMalhotra, AshutoshMangravite, Lara M.Maxwell, Taylor J.Merrill, EmilyNagorski, JohnNamasivayam, AishwaryaNarayan, ManjariNaz, MufassraNewhouse, Stephen J.Norman, Thea C.Nurtdinov, Ramil N.Oyang, Yen-JenPawitan, YudiPeng, ShengwenPeters, Mette A.Piccolo, Stephen R.Praveen, PaurushPriami, CorradoSabelnykova, Veronica Y.Senger, PhilippShen, XiaSimmons, AndrewSotiras, AristeidisStolovitzky, GustavoTangaro, SabinaTateo, AndreaTung, Yi-AnTustison, Nicholas J.Varol, ErdemVradenburg, GeorgeWeiner, Michael W.Xiao, GuanghuaXie, LeiXie, YangXu, JiaYang, HojinZhan, XiaoweiZhou, YunyunZhu, FanZhu, HongtuZhu, ShanfengAlzheimer’s Disease Neuroimaging Initiative2017-05-092017-05-092016Allen, Genevera I., Amoroso, Nicola, Anghel, Catalina, et al.. "Crowdsourced estimation of cognitive decline and resilience in Alzheimer's disease." <i>Alzheimer's & Dementia,</i> 12, no. 6 (2016) Elsevier: 645-653. https://doi.org/10.1016/j.jalz.2016.02.006.https://hdl.handle.net/1911/94205Identifying 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.engThis is an open access article under the CC BY-NC-ND licenseJournal articleAzheimer’s diseaseBiomarkersCrowdsourceBig dataBioinformaticsCognitive declineImagingGeneticshttps://doi.org/10.1016/j.jalz.2016.02.006