Developing, Applying, and Explaining Graph Convolutional Neural Networks in the Context of Genome Wide Association Analyses to Increase Attention Deficit/Hyperactivity Disorder Prediction Accuracy, Extract Novel Genomic Networks Associated With Attention
Developing, Applying, and Explaining Graph Convolutional Neural Networks in the Context of Genome Wide Association Analyses to Increase Attention Deficit/Hyperactivity Disorder Prediction Accuracy, Extract Novel Genomic Networks Associated With Attention
在全基因组关联分析的背景下开发、应用和解释图卷积神经网络，以提高注意力缺陷/多动症预测准确性，提取与注意力相关的新型基因组网络
批准号：
457223
负责人：
Saxena Ankita
金额：
$7.65万
依托单位国家：
加拿大
项目类别：
Studentship Programs
财政年份：
2021
资助国家：
加拿大
项目状态：
已结题
起止时间：
2021-10-01 至 2024-10-01
中文摘要
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英文摘要
Attention Deficit/Hyperactivity Disorder (ADHD) is a common psychiatric disorder that impairs patients' quality of life. Many factors, including genetics contribute to the disorder. Large scale studies of the genetics of people with and without ADHD have
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