Crowdsourced analysis of clinical trial data to predict amyotrophic lateral sclerosis progression

被引:0
|
作者
Robert Küffner
Neta Zach
Raquel Norel
Johann Hawe
David Schoenfeld
Liuxia Wang
Guang Li
Lilly Fang
Lester Mackey
Orla Hardiman
Merit Cudkowicz
Alexander Sherman
Gokhan Ertaylan
Moritz Grosse-Wentrup
Torsten Hothorn
Jules van Ligtenberg
Jakob H Macke
Timm Meyer
Bernhard Schölkopf
Linh Tran
Rubio Vaughan
Gustavo Stolovitzky
Melanie L Leitner
机构
[1] Institute of Bioinformatics and Systems Biology,Department of Informatics
[2] German Research Center for Environmental Health,Department of Statistics
[3] Ludwig-Maximilians-University,Department of Neuroscience
[4] Prize4Life,undefined
[5] Tel Aviv,undefined
[6] Israel and Cambridge,undefined
[7] Massachusetts,undefined
[8] USA.,undefined
[9] IBM T.J. Watson Research Center,undefined
[10] Yorktown Heights,undefined
[11] MGH Biostatistics Center,undefined
[12] Massachusetts General Hospital,undefined
[13] Harvard Medical School,undefined
[14] Sentrana Inc.,undefined
[15] Latham&Watkins LLP,undefined
[16] Stanford University,undefined
[17] Beaumont Hospital and Trinity College Dublin,undefined
[18] Neurological Clinical Research Institute,undefined
[19] Massachusetts General Hospital,undefined
[20] Luxembourg Centre for Systems Biomedicine,undefined
[21] University of Luxembourg,undefined
[22] Max Planck Institute for Intelligent Systems,undefined
[23] Institute of Social- and Preventive Medicine,undefined
[24] University of Zürich,undefined
[25] Orca XL Problem Solvers,undefined
[26] Max Planck Institute for Biological Cybernetics and Bernstein Center for Computational Neuroscience,undefined
[27] Berkeley School of Public Health,undefined
[28] University of California,undefined
[29] ALS Innovation Hub,undefined
[30] Biogen Idec,undefined
来源
Nature Biotechnology | 2015年 / 33卷
关键词
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中图分类号
学科分类号
摘要
An open competition to predict the progression of amyotrophic lateral sclerosis (ALS, also known as Lou Gehrig's disease) disease from the largest database of ALS clinical trial data yields potential new biomarkers and algorithms that outperform human clinicians.
引用
收藏
页码:51 / 57
页数:6
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