{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,7,25]],"date-time":"2024-07-25T00:31:49Z","timestamp":1721867509958},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643685274","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,7,24]],"date-time":"2024-07-24T00:00:00Z","timestamp":1721779200000},"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":[[2024,7,24]]},"abstract":"<jats:p>The MAUDE database is a valuable public resource for understanding malfunctions and adverse events related to medical devices and health IT. However, its extensive data and complex structure pose challenges. To overcome this, we have developed an automated analytical pipeline using GPT-4, a cutting-edge large language model. This pipeline is intended to efficiently extract, categorize, and visualize safety events with minimal human annotation. In our analysis of 4,459 colonoscopy reports from MAUDE (2011-2021), the events were categorized into operational, human factor, and device-related. Ishikawa diagrams visualized a subset stored in a vector database for easy retrieval and comparison through a similarity search. This innovative approach streamlines access to vital safety insights, reducing the workload on human annotators, and holds promise to enhance the utility of the MAUDE database.<\/jats:p>","DOI":"10.3233\/shti240155","type":"book-chapter","created":{"date-parts":[[2024,7,24]],"date-time":"2024-07-24T11:06:13Z","timestamp":1721819173000},"source":"Crossref","is-referenced-by-count":0,"title":["Enhancing MAUDE Database Utility by GPT-4 and Cause-Effect Visualization"],"prefix":"10.3233","author":[{"given":"Yue","family":"Yu","sequence":"first","affiliation":[{"name":"University of Texas Health Science Center at Houston"}]},{"given":"Yuheng","family":"Shi","sequence":"additional","affiliation":[{"name":"University of Texas Health Science Center at Houston"}]},{"given":"Yubo","family":"Feng","sequence":"additional","affiliation":[{"name":"Vanderbilt University"}]},{"given":"Yang","family":"Gong","sequence":"additional","affiliation":[{"name":"University of Texas Health Science Center at Houston"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","Innovation in Applied Nursing Informatics"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI240155","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,24]],"date-time":"2024-07-24T11:06:14Z","timestamp":1721819174000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI240155"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,7,24]]},"ISBN":["9781643685274"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti240155","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"value":"0926-9630","type":"print"},{"value":"1879-8365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,7,24]]}}}