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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Methodological considerations in designing and implementing the harmonized diagnostic assessment of dementia for
Joyita Banerjee1, Urvashi Jain2, Pranali Khobragade2
1Department of Geriatric Medicine, AllIndia Institute of Medical Sciences , New Delhi, India.
Abstract:
The Harmonized Diagnostic Assessment of Dementia for Longitudinal Aging Study in India (LASI-DAD) is a population-representative, prospective cohort study of late-life cognition and dementia. It is part of an ongoing international research collaboration that aims to measure and understand cognitive impairment and dementia risk by collecting a set of cognitive and neuropsychological assessments and informant reports, referred to as the Harmonized Cognitive Assessment Protocol (HCAP). LASI-DAD provides nationally representative data drawn from a subsample of the ongoing Longitudinal Aging Study in India (LASI). One of LASI-DAD's distinctive features is its rich geriatric assessment, including the collection of venous blood samples and brain imaging data for a subsample of respondents. In this paper, we discuss the methodological considerations of developing and implementing the HCAP protocol in India. The lessons we learned from translating and applying the HCAP protocol in an environment where illiteracy and innumeracy are high will provide important insights to researchers interested in measuring and collecting data on late-life cognition and dementia in developing countries. We further developed an innovative blood management system that enables us to follow the collection, transportation, assay, and storage of samples. Such innovation can benefit other population surveys collecting biomarker data.
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