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Previous works used many methods to discover regularities in prescriptions but rarely considered the actual therapeutic process in TCM and the information of herbs was ignored. In this work, we propose LAMGCN (Herb Recommendation via LSTMs with Attention Mechanisms and Graph Convolutional Networks), which takes the syndrome induction process and the herb descriptions into account. We utilize attention mechanisms and graph neural networks to capture the correlation between symptoms and herbs. Extensive experiments have been done and the results demonstrate the effectiveness of our proposed method.<\/jats:p>","DOI":"10.1145\/3708888","type":"journal-article","created":{"date-parts":[[2025,1,15]],"date-time":"2025-01-15T10:56:17Z","timestamp":1736938577000},"page":"1-22","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":7,"title":["LAMGCN:Traditional Chinese Medicine Herb Recommendation via LSTMs with Attention Mechanisms and Graph Convolutional Networks"],"prefix":"10.1145","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8601-802X","authenticated-orcid":false,"given":"Zhang","family":"Wenbo","sequence":"first","affiliation":[{"name":"Beijing University of Technology, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8382-8406","authenticated-orcid":false,"given":"Dang","family":"Hongbo","sequence":"additional","affiliation":[{"name":"Beijing University of Technology, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4714-8312","authenticated-orcid":false,"given":"Bao","family":"Zhenshan","sequence":"additional","affiliation":[{"name":"Beijing University of Technology, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-9003-6900","authenticated-orcid":false,"given":"Song","family":"Bingyan","sequence":"additional","affiliation":[{"name":"Beijing University of Technology, Beijing, China"}]}],"member":"320","published-online":{"date-parts":[[2025,3,11]]},"reference":[{"key":"e_1_3_1_2_2","doi-asserted-by":"publisher","unstructured":"Ashutosh Adhikari Ram Achyudh Raphael Tang William L. 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