arXiv (Cornell University) · 2018 · 101 citations · 20 references
MedicineNeurologyNeuroscienceDementiaForecastingNeurodegenerationAlzheimer DiseaseDementia DiagnosisDisease ForecastingDisease Progression ModelingNeurodegenerative DiseasesPredictive ModelingAlzheimer Disease ProgressionAlzheimer's Disease DiagnosisAlzheimer's Disease ModelsBenchmark DatasetsDisease Risk PredictionDisease Trajectory PredictionMachine Learning Prediction ModelsMonthly Forecasting
The Alzheimer's Disease Prediction Of Longitudinal Evolution (TADPOLE) Challenge compares the performance of algorithms at predicting future evolution of individuals at risk of Alzheimer's disease. TADPOLE Challenge participants train their models and algorithms on historical data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study or any other datasets to which they have access. Participants are then required to make monthly forecasts over a period of 5 years from January 2018, of three key outcomes for ADNI-3 rollover participants: clinical diagnosis, Alzheimer's Disease Assessment Scale Cognitive Subdomain (ADAS-Cog13), and total volume of the ventricles. These individual forecasts are later compared with the corresponding future measurements in ADNI-3 (obtained after the TADPOLE submission deadline). The first submission phase of TADPOLE was open for prize-eligible submissions between 15 June and 15 November 2017. The submission system remains open via the website: https://tadpole.grand-challenge.org, although since 15 November 2017 submissions are not eligible for the first round of prizes. This paper describes the design of the TADPOLE Challenge.
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Hypothetical model of dynamic biomarkers of the Alzheimer's pathological cascade
Clifford R. Jack, David S. Knopman, William J. Jagust et al. · The Lancet Neurology · 2009 · 4.8K citations · Full text
Alzheimer's Disease Neuroimaging Initiative (ADNI)
Ronald C. Petersen, Paul Aisen, Laurel Beckett et al. · Neurology · 2009 · 2.5K citations · Full text
Medicine, Neurology, Neuroscience +17
Within-subject template estimation for unbiased longitudinal image analysis
Martin Reuter, Nicholas J. Schmansky, H. Diana Rosas et al. · NeuroImage · 2012 · 2.5K citations · Full text
Neurodegenerative Diseases Target Large-Scale Human Brain Networks
William W. Seeley, Richard K. Crawford, Juan Zhou et al. · Neuron · 2009 · 2.4K citations · Full text