NIH R01 · 2024
Identifying Undiagnosed Alzheimer’s Disease in Understudied Populations
Project Abstract Diagnosis of Alzheimer’s disease (AD) is crucial for individuals to pursue treatments and plan for the future. Unfortunately, AD is underdiagnosed in community settings compared to the estimated prevalence from longitudinal cohort studies. AD underdiagnosis is exacerbated in understudied populations, including Hispanic/Latino (HL) and non-Hispanic African American (NH-AfAm) groups. Mining patients’ electronic health records (EHR) using machine learning may help identify patients with undiagnosed AD. Prior studies have identified individual comorbidities associated with AD. However, patients accumulate disease conditions sequentially accumulate over time. These pathways of…
From the public funding record at NIH RePORTER. Describes the funded project, not the reviews below.