BioKGrapher: Initial evaluation of automated knowledge graph construction from biomedical literature

Background The growth of biomedical literature presents challenges in extracting and structuring knowledge. Knowledge Graphs (KGs) offer a solution by representing relationships between biomedical entities. However, manual construction of KGs is labor-intensive and time-consuming, highlighting the n...

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Principais autores:	Henning Schäfer, Ahmad Idrissi-Yaghir, Kamyar Arzideh, Hendrik Damm, Tabea M.G. Pakull, Cynthia S. Schmidt, Mikel Bahn, Georg Lodde, Elisabeth Livingstone, Dirk Schadendorf, Felix Nensa, Peter A. Horn, Christoph M. Friedrich
Format:	Artigo
Jezik:	Inglês
Izdano:	Elsevier 2024-12-01
Serija:	Computational and Structural Biotechnology Journal
Teme:	Knowledge graph Named entity recognition Entity linking Clinical guidelines Software
Online dostop:	http://www.sciencedirect.com/science/article/pii/S2001037024003386
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