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Updated: Jul 2, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Delirium detection in clinical practice and research: critique of current tools and suggestions for future
1Department of Speech and Hearing Sciences, Indiana University, 200 South Jordan Avenue, Bloomington, IN 47405, USA. jakean@indiana.edu
Abstract:
Delirium is underrecognized clinically. Many tools have been developed to assist with the diagnosis of delirium, and they vary greatly in purpose, quality, and administration time. It is suggested that future development of delirium assessment instruments be guided by a dichotomization of raters into expert and nonexpert groups. Careful consideration of the needs of the two groups suggests that assessment instruments designed for nonexperts should be entirely objective, whereas those instruments developed for experts should include the full range of constructs associated with the syndrome. This conceptualization is explored in detail, and existing assessment instruments are considered briefly in light of this position.

