{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,30]],"date-time":"2026-01-30T06:59:26Z","timestamp":1769756366614,"version":"3.49.0"},"reference-count":56,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2023,5,16]],"date-time":"2023-05-16T00:00:00Z","timestamp":1684195200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Zhejiang Province Key Research and Development Project","award":["2020C03071"],"award-info":[{"award-number":["2020C03071"]}]},{"name":"Zhejiang Province Key Research and Development Project","award":["2021C03145"],"award-info":[{"award-number":["2021C03145"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Natural language processing (NLP) technology has played a pivotal role in health monitoring as an important artificial intelligence method. As a key technology in NLP, relation triplet extraction is closely related to the performance of health monitoring. In this paper, a novel model is proposed for joint extraction of entities and relations, combining conditional layer normalization with the talking-head attention mechanism to strengthen the interaction between entity recognition and relation extraction. In addition, the proposed model utilizes position information to enhance the extraction accuracy of overlapping triplets. Experiments on the Baidu2019 and CHIP2020 datasets demonstrate that the proposed model can effectively extract overlapping triplets, which leads to significant performance improvements compared with baselines.<\/jats:p>","DOI":"10.3390\/s23104812","type":"journal-article","created":{"date-parts":[[2023,5,17]],"date-time":"2023-05-17T01:58:06Z","timestamp":1684288686000},"page":"4812","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["A Joint Extraction System Based on Conditional Layer Normalization for Health Monitoring"],"prefix":"10.3390","volume":"23","author":[{"given":"Binbin","family":"Shi","sequence":"first","affiliation":[{"name":"School of Biological and Chemical Engineering, Zhejiang University of Science and Technology, Hangzhou 310023, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rongli","family":"Fan","sequence":"additional","affiliation":[{"name":"School of Biological and Chemical Engineering, Zhejiang University of Science and Technology, Hangzhou 310023, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lijuan","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Information and Electronic Engineering, Zhejiang University of Science and Technology, Hangzhou 310023, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jie","family":"Huang","sequence":"additional","affiliation":[{"name":"School of Information and Electronic Engineering, Zhejiang University of Science and Technology, Hangzhou 310023, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0394-4635","authenticated-orcid":false,"given":"Neal","family":"Xiong","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Mathematics Sul Ross State University, Alpine, TX 79830, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Athanasios","family":"Vasilakos","sequence":"additional","affiliation":[{"name":"Center for AI Research, University of Agder, 4879 Grimstad, Norway"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jian","family":"Wan","sequence":"additional","affiliation":[{"name":"School of Information and Electronic Engineering, Zhejiang University of Science and Technology, Hangzhou 310023, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lei","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Information and Electronic Engineering, Zhejiang University of Science and Technology, Hangzhou 310023, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,5,16]]},"reference":[{"key":"ref_1","first-page":"825","article-title":"The role of text analytics in healthcare: A review of recent developments and applications","volume":"5","author":"Elbattah","year":"2021","journal-title":"Healthinf"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Bose, P., Srinivasan, S., Sleeman, W.C., Palta, J., Kapoor, R., and Ghosh, P. 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