Matches in SemOpenAlex for { <https://semopenalex.org/work/W2009348550> ?p ?o ?g. }
Showing items 1 to 76 of
76
with 100 items per page.
- W2009348550 abstract "In progressive conditions like dementia, it is important to detect subtle cognitive changes early and initiate intervention to slow or even halt disease progression. Essential to early detection is comprehensive cognitive assessment. Computerized neuropsychological batteries offer rapid, standardized, and precise assessment, as well as automatic scoring, but it remains a formidable task to optimally integrate the information. This study aims to identify a machine learning (ML) algorithm that optimally and automatically integrates all available computerized cognitive testing scores to improve neuropsychological assessment of older adults. A dataset of 6136 individuals over age 50 who completed a computerized cognitive testing battery for mild impairment was used. 5108 individuals had a primary diagnosis of one of 81 neurological or psychiatric conditions (“neurological condition” group), and 1028 were cognitively healthy (control group). Four ML algorithms (Naive Bayes, multi-layer perceptron [MLP] neural network, support vector machine [SVM], decision tree) were compared in separating the neurological condition and control group using 65 raw cognitive scores, age and education. For the best performing algorithm, confidence in individual classifications and separation among diagnostic groups were evaluated. The MLP neural network approach best separated neurological condition and control group (area under the curve [AUC]=0.89; compare with AUC=0.70 for a single global cognitive score). In a test sample, maximum confidence (from MLP output node activity) was assigned in 76% of individuals classified as “neurological condition”, with 85% of these correctly classified. Maximum confidence was assigned in 71% of individuals classified as cognitively healthy, with 87% of these correctly classified. MLP performed well in separating the control group from mild cognitive impairment (MCI) (AUC=0.82), dementia (AUC=0.89), Parkinson's disease (AUC=0.91), multiple sclerosis (AUC=0.94), stroke (AUC=0.89), and traumatic brain injury (AUC=0.93), and showed good separation between amnestic MCI and Alzheimer's disease (AUC=0.75). ML algorithms may greatly improve the accuracy and efficiency of the neuropsychologist or cognitive expert in integrating the wealth of computerized cognitive scores with other clinical information in assessing older adults. Future work should evaluate ML algorithms that incorporate other clinical data as well as their potential utility in predicting conversion to MCI or dementia." @default.
- W2009348550 created "2016-06-24" @default.
- W2009348550 creator A5008565874 @default.
- W2009348550 creator A5050221351 @default.
- W2009348550 creator A5056692823 @default.
- W2009348550 creator A5086661201 @default.
- W2009348550 creator A5091361466 @default.
- W2009348550 date "2013-07-01" @default.
- W2009348550 modified "2023-09-27" @default.
- W2009348550 title "P3-219: A machine-learning approach for integration of computerized cognitive data in the neuropsychological assessment of older adults" @default.
- W2009348550 doi "https://doi.org/10.1016/j.jalz.2013.05.1292" @default.
- W2009348550 hasPublicationYear "2013" @default.
- W2009348550 type Work @default.
- W2009348550 sameAs 2009348550 @default.
- W2009348550 citedByCount "1" @default.
- W2009348550 countsByYear W20093485502017 @default.
- W2009348550 crossrefType "journal-article" @default.
- W2009348550 hasAuthorship W2009348550A5008565874 @default.
- W2009348550 hasAuthorship W2009348550A5050221351 @default.
- W2009348550 hasAuthorship W2009348550A5056692823 @default.
- W2009348550 hasAuthorship W2009348550A5086661201 @default.
- W2009348550 hasAuthorship W2009348550A5091361466 @default.
- W2009348550 hasBestOaLocation W20093485501 @default.
- W2009348550 hasConcept C118552586 @default.
- W2009348550 hasConcept C119857082 @default.
- W2009348550 hasConcept C12267149 @default.
- W2009348550 hasConcept C126322002 @default.
- W2009348550 hasConcept C14216870 @default.
- W2009348550 hasConcept C154945302 @default.
- W2009348550 hasConcept C15744967 @default.
- W2009348550 hasConcept C169900460 @default.
- W2009348550 hasConcept C179717631 @default.
- W2009348550 hasConcept C2779134260 @default.
- W2009348550 hasConcept C2779483572 @default.
- W2009348550 hasConcept C41008148 @default.
- W2009348550 hasConcept C44249647 @default.
- W2009348550 hasConcept C50644808 @default.
- W2009348550 hasConcept C52001869 @default.
- W2009348550 hasConcept C536788834 @default.
- W2009348550 hasConcept C71924100 @default.
- W2009348550 hasConceptScore W2009348550C118552586 @default.
- W2009348550 hasConceptScore W2009348550C119857082 @default.
- W2009348550 hasConceptScore W2009348550C12267149 @default.
- W2009348550 hasConceptScore W2009348550C126322002 @default.
- W2009348550 hasConceptScore W2009348550C14216870 @default.
- W2009348550 hasConceptScore W2009348550C154945302 @default.
- W2009348550 hasConceptScore W2009348550C15744967 @default.
- W2009348550 hasConceptScore W2009348550C169900460 @default.
- W2009348550 hasConceptScore W2009348550C179717631 @default.
- W2009348550 hasConceptScore W2009348550C2779134260 @default.
- W2009348550 hasConceptScore W2009348550C2779483572 @default.
- W2009348550 hasConceptScore W2009348550C41008148 @default.
- W2009348550 hasConceptScore W2009348550C44249647 @default.
- W2009348550 hasConceptScore W2009348550C50644808 @default.
- W2009348550 hasConceptScore W2009348550C52001869 @default.
- W2009348550 hasConceptScore W2009348550C536788834 @default.
- W2009348550 hasConceptScore W2009348550C71924100 @default.
- W2009348550 hasIssue "4S_Part_16" @default.
- W2009348550 hasLocation W20093485501 @default.
- W2009348550 hasOpenAccess W2009348550 @default.
- W2009348550 hasPrimaryLocation W20093485501 @default.
- W2009348550 hasRelatedWork W2383651644 @default.
- W2009348550 hasRelatedWork W2748952813 @default.
- W2009348550 hasRelatedWork W2787191226 @default.
- W2009348550 hasRelatedWork W2899084033 @default.
- W2009348550 hasRelatedWork W3168994312 @default.
- W2009348550 hasRelatedWork W3186233728 @default.
- W2009348550 hasRelatedWork W4205958290 @default.
- W2009348550 hasRelatedWork W4221021152 @default.
- W2009348550 hasRelatedWork W4327772909 @default.
- W2009348550 hasRelatedWork W4364301914 @default.
- W2009348550 hasVolume "9" @default.
- W2009348550 isParatext "false" @default.
- W2009348550 isRetracted "false" @default.
- W2009348550 magId "2009348550" @default.
- W2009348550 workType "article" @default.