Data Intelligence, Business Analytics
Predict the progression of disease in ALS patients based on the patient’s current disease status and clinical metadata.
This Challenge requires a written proposal and source code for prediction algorithm.
Given the current disease status for ALS patients, plus various clinical metadata (including patient demographics, medical and family history, functional measures, vital signs, and lab work), predict the progression of ALS disease.
Real-time online scoring is available for this Challenge. Using the online scoring system, Solvers can quickly score the accuracy of their own R code versus a blinded dataset, and compare performance versus other Solvers.
This Challenge has unique legal terms, please read the Challenge-Specific Agreement carefully. In summary, to receive an award, Solvers must submit a written proposal (i.e. description) and source code that validates the accuracy of a prediction algorithm. The award is contingent upon theoretical evaluation of the submissions by the Seeker. Solvers will NOT be required to transfer intellectual property to receive an award. Rather, receiving the full award will be contingent upon permission to submit the resultsand the algorithm to a peer reviewed scientific journal (for which the Seeker will pay the associated publication costs).
Data are made available with this Challenge solely for the purposes of advancing prediction of ALS disease progression. Any efforts to identify patients, sell the data, or use the data without permission, are strictly forbidden.