NMD-12: A new machine-learning derived screening instrument to detect mild cognitive impairment and dementia

文化大學機構典藏 CCUR > 體育運動健康學院 > 運動與健康促進學系 > 期刊論文 > Item 987654321/44640

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题名:	NMD-12: A new machine-learning derived screening instrument to detect mild cognitive impairment and dementia
作者:	Chiu, PY (Chiu, Pai-Yi) Tang, HP (Tang, Haipeng) Wei, CY (Wei, Cheng-Yu) Zhang, CY (Zhang, Chaoyang) Hung, GU (Hung, Guang-Uei) Zhou, WH (Zhou, Weihua)
贡献者:	運動與健康促進學系
关键词:	ALZHEIMERS ASSOCIATION WORKGROUPS AD8 INFORMANT INTERVIEW DIAGNOSTIC GUIDELINES NATIONAL INSTITUTE CUTOFF SCORES RELIABILITY VALIDITY DISEASE VERSION RECOMMENDATIONS
日期:	2019-05-08
上传时间:	2019-06-25 12:42:57 (UTC+8)
摘要:	Introduction Using machine learning techniques, we developed a brief questionnaire to aid neurologists and neuropsychologists in the screening of mild cognitive impairment (MCI) and dementia. Methods With the reduction of the survey size as a goal of this research, feature selection based on information gain was performed to rank the contribution of the 45 items corresponding to patient responses to the specified questions. The most important items were used to build the optimal screening model based on the accuracy, practicality, and interpretability. The diagnostic accuracy for discriminating normal cognition (NC), MCI, very mild dementia (VMD) and dementia was validated in the test group. Results The screening model (NMD-12) was constructed with the 12 items that were ranked the highest in feature selection. The receiver-operator characteristic (ROC) analysis showed that the area under the curve (AUC) in the test group was 0.94 for discriminating NC vs. MCI, 0.88 for MCI vs. VMD, 0.97 for MCI vs. dementia, and 0.96 for VMD vs. dementia, respectively. Discussion The NMD-12 model has been developed and validated in this study. It provides healthcare professionals with a simple and practical screening tool which accurately differentiates NC, MCI, VMD, and dementia.
關聯:	PLoS ONE 14(3): e0213430
显示于类别:	[運動與健康促進學系] 期刊論文

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