{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T15:11:18Z","timestamp":1775833878811,"version":"3.50.1"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643685335","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,8,22]],"date-time":"2024-08-22T00:00:00Z","timestamp":1724284800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,8,22]]},"abstract":"<jats:p>Hand-labelling clinical corpora can be costly and inflexible, requiring re-annotation every time new classes need to be extracted. PICO (Participant, Intervention, Comparator, Outcome) information extraction can expedite conducting systematic reviews to answer clinical questions. However, PICO frequently extends to other entities such as Study type and design, trial context, and timeframe, requiring manual re-annotation of existing corpora. In this paper, we adapt Snorkel\u2019s weak supervision methodology to extend clinical corpora to new entities without extensive hand labelling. Specifically, we enrich the EBM-PICO corpus with new entities through an example of \u201cStudy type and design\u201d extraction. Using weak supervision, we obtain programmatic labels on 4,081 EBM-PICO documents, achieving an F1-score of 85.02% on the test set.<\/jats:p>","DOI":"10.3233\/shti240775","type":"book-chapter","created":{"date-parts":[[2024,8,23]],"date-time":"2024-08-23T10:42:36Z","timestamp":1724409756000},"source":"Crossref","is-referenced-by-count":3,"title":["PICO to PICOS: Weak Supervision to Extend Datasets with New Labels"],"prefix":"10.3233","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1691-1338","authenticated-orcid":false,"given":"Anjani","family":"Dhrangadhariya","sequence":"first","affiliation":[{"name":"Informatics Institute, HES-SO Valais-Wallis, Switzerland"},{"name":"University of Geneva (UNIGE), Geneva, Switzerland"}]},{"given":"Gaetano","family":"Manzo","sequence":"additional","affiliation":[{"name":"Computational Health Research Branch, NLM, Bethesda, Maryland, USA"}]},{"given":"Henning","family":"M\u00fcller","sequence":"additional","affiliation":[{"name":"Informatics Institute, HES-SO Valais-Wallis, Switzerland"},{"name":"University of Geneva (UNIGE), Geneva, Switzerland"},{"name":"The Sense research and innovation center, Lausanne and Sion, Switzerland"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","Digital Health and Informatics Innovations for Sustainable Health Care Systems"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI240775","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,23]],"date-time":"2024-08-23T10:42:36Z","timestamp":1724409756000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI240775"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8,22]]},"ISBN":["9781643685335"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti240775","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"value":"0926-9630","type":"print"},{"value":"1879-8365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,8,22]]}}}