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The goal of this challenge is to predict the progression of disease in ALS patients based on the patient’s current disease status. The data available to make this prediction includes demographics, medical and family history data, functional measures, vital signs, and lab data (blood chemistry/hematology/urinalysis). These data have been obtained from industry, academic, and government-funded clinical trials. The awarded prize was $50,000.

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Crowdsourced analysis of clinical trial data to predict amyotrophic lateral sclerosis progression
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
Nature Biotechnology (Published online Nov. 2, 2015)

Link to Nature Biotechnology