Machine learning prediction algorithms for 2- , 5- and 10-year risk of Alzheimer's, Parkinson's and dementia at age 65: a study using medical records from France and the UK General Practitioners.

Background: Leveraging machine learning on electronic health records offers a promising method for early identification of individuals at risk for dementia and neurodegenerative diseases. Current risk algorithms heavily rely on age, highlighting the need for alternative models with strong predictive power, especially at age 65, a crucial time for early screening and prevention.

Methods: This prospective study analyzed electronic health records (EHR) from 76,427 adults (age 65, 52.

Ten years preceding a diagnosis of neurodegenerative disease in Europe and Australia: medication use, health conditions, and biomarkers associated with Alzheimer's disease, Parkinson's disease, and amyotrophic lateral sclerosis.

Background: Many studies have investigated early predictors for Alzheimer's disease (AD), Parkinson's disease (PD), and amyotrophic lateral sclerosis (ALS). However, evidence is sparse regarding specific and common predictors for these diseases. We aimed to identify medication use, health conditions, and blood biomarkers that might be associated with the risk of AD, PD, and ALS ten years later.