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Updated: Jul 10, 2025

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

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随机生存森林在预测从轻度认知障碍到阿尔茨海默病转化风险方面的解释性

Alessia Sarica1, Federica Aracri2, Maria Giovanna Bianco2

  • 1Neuroscience Research Center, Department of Medical and Surgical Sciences, Magna Graecia University, viale Europa, loc. Germaneto, 88100, Catanzaro, Italy. sarica@unicz.it.

Brain informatics
|November 18, 2023
PubMed
概括

随机生存森林 (RSF) 准确地预测阿尔茨海默病 (AD) 从轻度认知障碍 (MCI) 的进展. 沙普利添加剂解释 (SHAP) 提高了RSF的解释性,识别了临床决策的关键生物标志物.

关键词:
阿尔茨海默病进展的进展考克斯的比例危险性痴呆症的风险 痴呆症的风险在MCI转换转换过程中,MCI机器学习是机器学习.随机生存森林 随机生存森林对生存分析的分析.

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