Adapting State-of-the-Art Deep Language Models to Clinical Information Extraction Systems: Potential...
Adapting State-of-the-Art Deep Language Models to Clinical Information Extraction Systems: Potentials, Challenges, and Solutions
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Publisher
Canada: JMIR Publications
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Language
English
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Canada: JMIR Publications
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Contents
Deep learning (DL) has been widely used to solve problems with success in speech recognition, visual object recognition, and object detection for drug discovery and genomics. Natural language processing has achieved noticeable progress in artificial intelligence. This gives an opportunity to improve on the accuracy and human-computer interaction of...
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Full title
Adapting State-of-the-Art Deep Language Models to Clinical Information Extraction Systems: Potentials, Challenges, and Solutions
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TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_6658232
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_6658232
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ISSN
2291-9694
E-ISSN
2291-9694
DOI
10.2196/11499
