Show pageBacklinksCite current pageExport to PDFBack to top This page is read only. You can view the source, but not change it. Ask your administrator if you think this is wrong. The exponential growth of the number of medical [[publication]]s makes it more and more difficult for the clinical practitioner to keep track of relevant scientific progress. Computer aided screening and analysis might help to overview and classify the content of medical publications more efficiently. The new wave of enthusiasm for [[machine learning algorithm]]s has launched several new possibilities to analyze and categorize [[document]]s, ranging from sports news to hospital [[discharge]] summaries. Search [[algorithm]]s for the medical [[literature]], i.e. [[PubMed]] are based on keywords and full text search. The U.S. National Library of Medicine and National Institutes of Health have made great effort to implement semantics into their data structure ((UMLS terminology services - A service of the U.S. national library of medicine, National Institutes of Health, https://uts.nlm.nih.gov/home.html/. Accessed 4 April 2020.)). Most of the concepts base on the [[W3C]] ideas and standards ((W3C Standards, http://www.w3.org/standards/. Accessed 4 April 2020)). w3c.txt Last modified: 2024/06/07 02:58by 127.0.0.1