Detection of cognitive impairment using a machine-learning algorithm

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Detection of cognitive impairment using a machine-learning algorithm

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im November 2018 veröffentlichter wissenschaftlicher Artikel

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scientific article published on 01 November 2018

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wetenschappelijk artikel

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наукова стаття, опублікована в листопаді 2018

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Detection of cognitive impairment using a machine-learning algorithm

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Detection of cognitive impairment using a machine-learning algorithm

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Detection of cognitive impairment using a machine-learning algorithm

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Detection of cognitive impairment using a machine-learning algorithm

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Detection of cognitive impairment using a machine-learning algorithm

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Detection of cognitive impairment using a machine-learning algorithm

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Detection of cognitive impairment using a machine-learning algorithm

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Ging-Yuek Robin Hsiung

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Jason J Jung

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Ko Woon Kim

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SangYun Kim

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Seong Hye Choi

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Young Chul Youn

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“Mini-mental state”

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Machine learning for medical diagnosis: history, state of the art and perspective

Seoul Neuropsychological Screening Battery-dementia version (SNSB-D): a useful tool for assessing and monitoring cognitive impairments in dementia patients.

Machine-learning techniques for building a diagnostic model for very mild dementia

Population-based norms for the Mini-Mental State Examination by age and educational level.

Tissue-based Alzheimer gene expression markers-comparison of multiple machine learning approaches and investigation of redundancy in small biomarker sets

Clinical characteristics of a nationwide hospital-based registry of mild-to-moderate Alzheimer's disease patients in Korea: a CREDOS (Clinical Research Center for Dementia of South Korea) study.

MRI-Based Classification Models in Prediction of Mild Cognitive Impairment and Dementia in Late-Life Depression.

Dementia risk prediction in the population: are screening models accurate?

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2939-2945

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scholarly article

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10.2147/NDT.S171950

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English

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Jae-Won Jang

Hae-Won Shin

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2018-11-01T00:00:00Z

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30464478

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6219269

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