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Knowledge-Based Biomedical Data Science.
Callahan, Tiffany J; Tripodi, Ignacio J; Pielke-Lombardo, Harrison; Hunter, Lawrence E.
Afiliación
  • Callahan TJ; Computational Bioscience Program and Department of Pharmacology, University of Colorado Denver Anschutz Medical Campus, Aurora, Colorado 80045, USA.
  • Tripodi IJ; Department of Computer Science, University of Colorado, Boulder, Colorado 80309, USA.
  • Pielke-Lombardo H; Computational Bioscience Program and Department of Pharmacology, University of Colorado Denver Anschutz Medical Campus, Aurora, Colorado 80045, USA.
  • Hunter LE; Computational Bioscience Program and Department of Pharmacology, University of Colorado Denver Anschutz Medical Campus, Aurora, Colorado 80045, USA.
Annu Rev Biomed Data Sci ; 3: 23-41, 2020 Jul.
Article en En | MEDLINE | ID: mdl-33954284
Knowledge-based biomedical data science 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 recent progress in systems that use formally represented knowledge to address data science problems in both clinical and biological domains, as well as progress on approaches for creating knowledge graphs. Major themes include the relationships between knowledge graphs and machine learning, the use of natural language processing to construct knowledge graphs, and the expansion of novel knowledge-based approaches to clinical and biological domains.
Palabras clave

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Annu Rev Biomed Data Sci Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Annu Rev Biomed Data Sci Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos
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