Combining supervised and unsupervised named entity recognition to detect psychosocial risk factors in occupational health checks-Reference-Cited by-同舟云学术

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Combining supervised and unsupervised named entity recognition to detect psychosocial risk factors in occupational health checks

Published:2022-04 Issue: Volume:160 Page:104695
ISSN:1386-5056
Container-title:International Journal of Medical Informatics
language:en
Short-container-title:International Journal of Medical Informatics

Author:

Uronen L.^ORCID,Salanterä S.,Hakala K.,Hartiala J.^ORCID,Moen H.^ORCID

Publisher

Elsevier BV

Subject

Health Informatics

Reference28 articles.

1. Psychosocial work factor and long sickness absence in Europe;Slany;Int. J. Occ. Env. Health.,2014

2. Job satisfaction and intention to quit the job;Suadicani;Occ. Med.,2013

3. The impact of psychosocial work environment factors on the risk of disability pension in Denmark;Christensen;Eur. J. Public Health,2008

4. Working conditions as risk factors for disability retirement: a longitudinal register linkage study;Lahelma;BMC Public Health,2012

5. Work arrangements, physical working conditions, and psychosocial working conditions as risk factors for sickness absence: Bayesian analysis of prospective data;Laaksonen;Ann. Epidemiol.,2010

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Text data labeling process for semi-supervised learning modeling;AIP Conference Proceedings;2024

2. Named Entity Recognition in Electronic Health Records: A Methodological Review;Healthcare Informatics Research;2023-10-31

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