Identification of Patterns of Cognitive Impairment for Early Detection of Dementia

Anusha, AS and Ranjan, U and Sharma, M and Dutt, S (2020) Identification of Patterns of Cognitive Impairment for Early Detection of Dementia. In: 42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society, EMBC, 20-24 July 2020, Montreal; Canada, pp. 5498-5501.

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Abstract

Early detection of dementia is crucial to devise effective interventions. Comprehensive cognitive tests, while being the most accurate means of diagnosis, are long and tedious, thus limiting their applicability to a large population, especially when periodic assessments are needed. The problem is compounded by the fact that people have differing patterns of cognitive impairment as they progress to different forms of dementia. This paper presents a novel scheme by which individual-specific patterns of impairment can be identified and used to devise personalized tests for periodic follow-up. Patterns of cognitive impairment are initially learned from a population cluster of combined normals and cognitively impaired subjects, using a set of standardized cognitive tests. Impairment patterns in the population are identified using a 2step procedure involving an ensemble wrapper feature selection followed by cluster identification and analysis. These patterns have been shown to correspond to clinically accepted variants of Mild Cognitive Impairment (MCI), a prodrome of dementia. The learned clusters of patterns can subsequently be used to identify the most likely route of cognitive impairment, even for pre-symptomatic and apparently normal people. Baseline data of 24,000 subjects from the NACC database was used for the study. © 2020 IEEE.

Item Type:	Conference Paper
Publication:	Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Publisher:	Institute of Electrical and Electronics Engineers Inc.
Additional Information:	The copyright of this article belongs to Institute of Electrical and Electronics Engineers Inc.
Keywords:	Diagnosis, Baseline data; Cognitive impairment; Cognitive tests; Cognitively impaired; Large population; Mild cognitive impairments (MCI); Most likely; Periodic assessment, Neurodegenerative diseases
Department/Centre:	Autonomous Societies / Centres > Centre for Brain Research
Date Deposited:	29 Sep 2020 10:07
Last Modified:	29 Sep 2020 10:07
URI:	http://eprints.iisc.ac.in/id/eprint/66682

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