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Existing imaging genetic studies usually has the problem of inefficiency and inadequate fusion of data. This study proposes a novel deep learning method to efficiently capture the development pattern of AD. First, we model the interaction between brain regions and genes as node-to-node feature aggregation in a brain region\u2013gene network. Second, we propose a feature aggregation graph convolutional network (FAGCN) to transmit and update the node feature. Compared with the trivial graph convolutional procedure, we replace the input from the adjacency matrix with a weight matrix based on correlation analysis and consider common neighbor similarity to discover broader associations of nodes. Finally, we use a full-gradient saliency graph mechanism to score and extract the pathogenetic brain regions and risk genes. According to the results, FAGCN achieved the best performance among both traditional and cutting-edge methods and extracted AD-related brain regions and genes, providing theoretical and methodological support for the research of related diseases.<\/jats:p>","DOI":"10.1093\/bib\/bbac137","type":"journal-article","created":{"date-parts":[[2022,4,14]],"date-time":"2022-04-14T11:16:25Z","timestamp":1649934985000},"source":"Crossref","is-referenced-by-count":23,"title":["Feature aggregation graph convolutional network based on imaging genetic data for diagnosis and pathogeny identification of Alzheimer\u2019s disease"],"prefix":"10.1093","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2715-3360","authenticated-orcid":false,"given":"Xia-an","family":"Bi","sequence":"first","affiliation":[{"name":"Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing, and the College of Information Science and Engineering in Hunan Normal University, P.R. China"}]},{"given":"Wenyan","family":"Zhou","sequence":"additional","affiliation":[{"name":"College of Information Science and Engineering, Hunan Normal University, Changsha, China"}]},{"given":"Sheng","family":"Luo","sequence":"additional","affiliation":[{"name":"College of Information Science and Engineering, Hunan Normal University, Changsha, China"}]},{"given":"Yuhua","family":"Mao","sequence":"additional","affiliation":[{"name":"College of Information Science and Engineering, Hunan Normal University, Changsha, China"}]},{"given":"Xi","family":"Hu","sequence":"additional","affiliation":[{"name":"College of Information Science and Engineering, Hunan Normal University, Changsha, China"}]},{"given":"Bin","family":"Zeng","sequence":"additional","affiliation":[{"name":"Hunan Youdao Information Technology Co., Ltd, P.R. China"}]},{"given":"Luyun","family":"Xu","sequence":"additional","affiliation":[{"name":"College of Business in Hunan Normal University, P.R. 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