大学研究人员开发89-95%准确的TBM系统,以识别脑图象中的自闭症基因标记。 University researchers develop 89-95% accurate TBM system to identify autism genetic markers in brain images.

弗吉尼亚大学的研究人员与加州大学旧金山分校和约翰霍普金斯大学一起开发了一种称为基于运输的形态测量法（TBM）的系统，可以以 89-95% 的准确率识别大脑图像中自闭症的遗传标记。 University of Virginia researchers, along with UCSF and Johns Hopkins, have developed a system called Transport-Based Morphometry (TBM) to identify genetic markers of autism in brain images with 89-95% accuracy. 这一技术使用数学模型来区分正常的大脑结构变化和与自闭症相关影印数变化有关的大脑结构变化。 This technique uses mathematical models to distinguish normal brain structure variations from those linked to autism-related copy number variations (CNVs). 这一突破可能导致对自闭症进行早期诊断和个性化治疗。 The breakthrough could lead to earlier diagnoses and personalized treatments for autism.

August 28, 2024

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