Crowdsourced estimation of cognitive decline and resilience in Alzheimer's disease

Identifying 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

Policy Paper on Healthy Ageing

Populations around the world are ageing faster than ever in the past. A constant and already impressive rate in the worldwide increase of life expectancy has led to the fact that the current proportion of the population above 60 years (17%) will double in the next thirty to forty years. In the next 30 years, every third person in the world will fall into the category of a senior citizen. Tis demographic transition will have an impact on almost all aspects of society and requires a complete and well-defned shif in the paradigm in the medical, social, and technological felds. Croatia’s Presidency of the Council of the European Union 2020 highlighted demographic challenges and ageing as important issues. Under the Horizon 2020 Work Programme Health, demographic change and wellbeing 2018–2020 call 10 within the section “Other actions”, a conference Better Future of Healthy Ageing 2020 (BFHA 2020) took place as a part of “Croatian Presidency event – Innovation for better ageing”, organized by the University of Zagreb School of Medicine at the Andrija Štampar School of Public Health

Crowdsourced estimation of cognitive decline and resilience in Alzheimer's disease.

Identifying 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

Crowdsourced estimation of cognitive decline and resilience in Alzheimer's disease

Identifying 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