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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Alzheimer's Disease in Primary Care: The Significance of Early Detection, Diagnosis, and Intervention
Lawrence Herman1, Alireza Atri2, Stephen Salloway3
1Dean, Professor and Program Director, Physician Assistant Studies, Gardner-Webb University, College of Health Sciences, Boiling Springs, North Carolina.
Abstract:
The field of Alzheimer's disease (AD) is undergoing a profound and rapid change: clinical trials have been redesigned to focus on individuals in the earliest stages of the disease and are including more sensitive measurement tools to better capture changes in cognition and other outcomes. (Online access: http://courses.elseviercme.com/adwebcast/674http://courses.elseviercme.com/alzheimer/593e). Trial participants undergo PET imaging for amyloid load as a hallmark for dementia, as well as genetic testing to determine likelihood of disease progression and response to therapeutic intervention. Large national and international registries have been established to capture those at risk and to follow their development of cognitive changes longitudinally. Understanding that the disease process starts at least a decade or more before the onset of symptoms has prompted the development of therapeutic interventions acting very early in the disease cascade. For all these reasons, recognizing and diagnosing AD early offers affected individuals and their caregivers the best chance for care planning, access to available symptomatic treatment and community resources, as well as involvement with clinical trials and access to new therapies when they become available. Primary care clinicians play a pivotal role in the early recognition of cognitive impairment in their patients.
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