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A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

Article DOI: 10.3791/58392-v • 07:50 min • September 20th, 2018
September 20th, 2018 •
1,2, 1,2,3, 1,2, 4, 1,3, 1,5,6,7, 1,7,8,9, 1,2,3,7,8
1The NIH BD2K Center of Excellence in Biomedical Computing, University of California, Los Angeles, 2Department of Physiology, University of California, Los Angeles, 3Department of Medicine/Cardiology, University of California, Los Angeles, 4Department of Cardiology, First Affiliated Hospital, Zhejiang University School of Medicine, 5Department of Radiological Sciences, University of California, Los Angeles, 6Department of Bioengineering, University of California, Los Angeles, 7Scalable Analytics Institute (ScAi), University of California, Los Angeles, 8Department of Bioinformatics, University of California, Los Angeles, 9Department of Computer Science, University of California, Los Angeles

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We present a protocol and associated metadata template for the extraction of text describing biomedical concepts in clinical case reports. The structured text values produced through this protocol can support deep analysis of thousands of clinical narratives.

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Metadata Extraction Clinical Case Reports Biomedical Concepts Disease Symptoms Diagnostic Procedures Therapeutic Procedures Patient Outcomes Epidemiological Studies Rare Conditions Emerging Conditions Text Analysis Workflows Machine Readable Data Rich Metadata Findable Accessible Interoperable Reusable Data Resource Metadata Template Clinical Information Extraction Clinical Case Report Corpus Contextual Details Controlled Vocabulary Annotation Template Key Terms Demographic Values
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