Knowledge-based Biomedical Data Science 2019
October 08, 2019 Β· Declared Dead Β· π Annual Review of Biomedical Data Science
"No code URL or promise found in abstract"
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Authors
Tiffany J. Callahan, Harrison Pielke-Lombardo, Ignacio J. Tripodi, Lawrence E. Hunter
arXiv ID
1910.06710
Category
cs.AI: Artificial Intelligence
Cross-listed
cs.CL
Citations
38
Venue
Annual Review of Biomedical Data Science
Last Checked
4 months ago
Abstract
Knowledge-based biomedical data science (KBDS) involves the design and implementation of computer systems that act as if they knew about biomedicine. Such systems depend on formally represented knowledge in computer systems, often in the form of knowledge graphs. Here we survey the progress in the last year in systems that use formally represented knowledge to address data science problems in both clinical and biological domains, as well as on approaches for creating knowledge graphs. Major themes include the relationships between knowledge graphs and machine learning, the use of natural language processing, and the expansion of knowledge-based approaches to novel domains, such as Chinese Traditional Medicine and biodiversity.
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