ArticleAmerican journal of Alzheimer's disease and other dementias
Machine-Learning Algorithms Based on Screening Tests for Mild Cognitive Impairment.
Article in American journal of Alzheimer's disease and other dementias. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Artificial Intelligence for the Early Detection of Patients with Cognitive Impairment: A Scoping Review.Healthcare (Basel, Switzerland) · 2026Review
- Detection of mild cognitive impairment using a virtual reality-based stroop task: a cross-sectional study of embodied behavioral markers.Journal of neuroengineering and rehabilitation · 2025Observational
- Diabetic retinopathy as the primary predictor of mild cognitive impairment in type 2 diabetes: Insights from machine learning models.PloS one · 2025Article
- Creation and verification of a predictive nomogram model for the incidence of social isolation among China's older population.Frontiers in public health · 2025Article
- Discriminant Power of Smartphone-Derived Keystroke Dynamics for Mild Cognitive Impairment Compared to a Neuropsychological Screening Test: Cross-Sectional Study.Journal of medical Internet research · 2024Article
- Classification of Mild Cognitive Impairment Using Functional Near-Infrared Spectroscopy-Derived Biomarkers With Convolutional Neural Networks.Psychiatry investigation · 2024Article
- Non-equivalence of sub-tasks of the Rey-Osterrieth Complex Figure Test with convolutional neural networks to discriminate mild cognitive impairment.BMC psychiatry · 2024Article
- Applications of Artificial Intelligence in the Neuropsychological Assessment of Dementia: A Systematic Review.Journal of personalized medicine · 2024Review
- Mental workload classification using convolutional neural networks based on fNIRS-derived prefrontal activity.BMC neurology · 2023Article
- Effects of Personalized Cognitive Training Using Mental Workload Monitoring on Executive Function in Older Adults With Mild Cognitive Impairment.Brain & NeuroRehabilitation · 2023Article
- In-hospital fall prediction using machine learning algorithms and the Morse fall scale in patients with acute stroke: a nested case-control study.BMC medical informatics and decision making · 2023Article
- Can the fNIRS-derived neural biomarker better discriminate mild cognitive impairment than a neuropsychological screening test?Frontiers in aging neuroscience · 2023Article
- Can the Virtual Reality-Based Spatial Memory Test Better Discriminate Mild Cognitive Impairment than Neuropsychological Assessment?International journal of environmental research and public health · 2022Article
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1 author.
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Abstract
backgroundThe mobile screening test system for mild cognitive impairment (mSTS-MCI) was developed and validated to address the low sensitivity and specificity of the Montreal Cognitive Assessment (MoCA) widely used clinically.
objectiveThis study was to evaluate the efficacy machine learning algorithms based on the mSTS-MCI and Korean version of MoCA.
methodIn total, 103 healthy individuals and 74 patients with MCI were randomly divided into training and test data sets, respectively. The algorithm using TensorFlow was trained based on the training data set, and then its accuracy was calculated based on the test data set. The cost was calculated via logistic regression in this case.
resultPredictive power of the algorithms was higher than those of the original tests. In particular, the algorithm based on the mSTS-MCI showed the highest positive-predictive value.
conclusionThe machine learning algorithms predicting MCI showed the comparable findings with the conventional screening tools.
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