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Identification of infants at high familiar risk for language-learning disorders (LLD) by combining machine learning techniques with EEG-based brain network metrics Editorial

机译：通过将机器学习技术与基于脑电图的脑网络指标相结合，识别处于高度熟悉的语言学习障碍（LLD）风险的婴儿编辑

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Dimitriadis Stavros;
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年度 2016
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正文语种 en
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1. Identification of infants at high familiar risk for language-learning disorders (LLD) by combining machine learning techniques with EEG-based brain network metrics [J] . Dimitriadis Stavros I. Clinical neurophysiology . 2016,第7期

机译：通过将机器学习技术与基于EEG的脑网络指标相结合来识别处于高度熟悉的语言学习障碍（LLD）风险的婴儿
2. Determining the effects of LLD and MCI on brain decline according to machine learning and a structural covariance network analysis [J] . Journal of psychiatric research . 2020,第期

机译：根据机器学习和结构协方差网络分析，确定LLD和MCI对脑下降的影响
3. Machine learning classifier using abnormal brain network topological metrics in major depressive disorder [J] . GuoH., CaoX., LiuZ., Neuroreport . 2012,第17期

机译：在重度抑郁症中使用异常脑网络拓扑指标的机器学习分类器
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Identification of infants at high familiar risk for language-learning disorders (LLD) by combining machine learning techniques with EEG-based brain network metrics Editorial

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