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Some current state-of-the-art distributed representation methods, including Convolutional Neural Network (CNN), Bi-directional Long Short Term Memory networks (Bi-LSTM) and Bidirectional Encoder Representations from Transformers (BERT), were used in our framework, and a system based on this framework was developed for a shared task regarding clinical STS organized by BioCreative\/OHNLP in 2018.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Compared with the systems only using distributed representation or one-hot representation, our method achieved much higher Pearson correlation. Among all distributed representations, BERT performed best. The highest Person correlation of our system was 0.8541, higher than the best official one of the BioCreative\/OHNLP clinical STS shared task in 2018 (0.8328) by 0.0213.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>Distributed representation and one-hot representation are complementary to each other and can be fused by gated network.<\/jats:p><\/jats:sec>","DOI":"10.1186\/s12911-020-1045-z","type":"journal-article","created":{"date-parts":[[2020,4,30]],"date-time":"2020-04-30T00:02:58Z","timestamp":1588204978000},"update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":27,"title":["Distributed representation and one-hot representation fusion with gated network for clinical semantic textual similarity"],"prefix":"10.1186","volume":"20","author":[{"given":"Ying","family":"Xiong","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shuai","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haoming","family":"Qin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"He","family":"Cao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yedan","family":"Shen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaolong","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qingcai","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jun","family":"Yan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Buzhou","family":"Tang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,4,30]]},"reference":[{"key":"1045_CR1","unstructured":"Zhang R, Pakhomov S, McInnes BT, Melton GB. 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