{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,22]],"date-time":"2025-02-22T05:35:40Z","timestamp":1740202540548,"version":"3.37.3"},"reference-count":0,"publisher":"IOS Press","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017]]},"abstract":"<jats:p>The online patient question and answering (Q&amp;amp;A) system, either as a website or a mobile application, attracts an increasing number of users in China. Patients will post their questions and the registered doctors then provide the corresponding answers. A large amount of questions with answers from doctors are accumulated. Instead of awaiting the response from a doctor, the newly posted question could be quickly answered by finding a semantically equivalent question from the Q&amp;amp;A achive. In this study, we investigated a novel deep learning based method to retrieve the similar patient question in Chinese. An unsupervised learning algorithm using deep neural network is performed on the corpus to generate the word embedding. The word embedding was then used as the input to a supervised learning algorithm using a designed deep neural network, i.e. the supervised neural attention model (SNA), to predict the similarity between two questions. The experimental results showed that our SNA method achieved P@1 = 77% and P@5 = 84%, which outperformed all other compared methods.<\/jats:p>","DOI":"10.3233\/978-1-61499-830-3-604","type":"book-chapter","created":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T15:26:30Z","timestamp":1740151590000},"source":"Crossref","is-referenced-by-count":0,"title":["A Deep Learning-Based Method for Similar Patient Question Retrieval in Chinese"],"prefix":"10.3233","author":[{"family":"Tang Guo Yu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"family":"Ni Yuan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"family":"Xie Guo Tong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"family":"Fan Xin Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"family":"Shi Yan Ling","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","MEDINFO 2017: Precision Healthcare through Informatics"],"original-title":[],"deposited":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T16:23:02Z","timestamp":1740154982000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.medra.org\/servlet\/aliasResolver?alias=iospressISBN&isbn=978-1-61499-829-7&spage=604&doi=10.3233\/978-1-61499-830-3-604"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017]]},"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/978-1-61499-830-3-604","relation":{},"ISSN":["0926-9630"],"issn-type":[{"value":"0926-9630","type":"print"}],"subject":[],"published":{"date-parts":[[2017]]}}}