ArticleAlzheimer's & dementia (Amsterdam, Netherlands)
Dementia ascertainment in India and development of nation-specific cutoffs: A machine learning and diagnostic analysis.
Article in Alzheimer's & dementia (Amsterdam, Netherlands). The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Dementia ascertainment in India and development of nation-specific cutoffs: A machine learning and diagnostic analysis.Alzheimer's & dementia (Amsterdam, Netherlands)Article
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6 authors.
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Abstract
Introduction: Cognitive assessments are useful in ascertaining dementia but may be influenced by patient characteristics. India's distinct culture and demographics warrant investigation into population-specific cutoffs. Methods: Data were utilized from the Longitudinal Aging Study in India-Diagnostic Assessment of Dementia ( Results: The Informant Questionnaire of Cognitive Decline in the Elderly (IQCODE) and Hindi Mini-Mental State Examination (HMSE) were identified as the most impactful assessments with optimal cutoffs of 3.8 and 25, respectively. Discussion: An ML assessment of clinician dementia ratings identified IQCODE and HMSE to be the most impactful assessments. Optimal cutoffs of 3.8 and 25 were identified and performed excellently in the overall sample, though did decrease in specific, more difficult-to-diagnose subgroups. Highlights: Pioneers use of explainable artificial intelligence in the diagnosis of dementia.Creates assessment cutoffs specific to the nation of India.Highlights differences in cutoffs across nations.
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