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KGHC: a knowledge graph for hepatocellular carcinoma.
- Source :
- BMC Medical Informatics & Decision Making; 7/9/2020 Supplement 3, Vol. 20, p1-11, 11p, 5 Diagrams, 3 Charts, 3 Graphs
- Publication Year :
- 2020
-
Abstract
- <bold>Background: </bold>Hepatocellular carcinoma is one of the most general malignant neoplasms in adults with high mortality. Mining relative medical knowledge from rapidly growing text data and integrating it with other existing biomedical resources will provide support to the research on the hepatocellular carcinoma. To this purpose, we constructed a knowledge graph for Hepatocellular Carcinoma (KGHC).<bold>Methods: </bold>We propose an approach to build a knowledge graph for hepatocellular carcinoma. Specifically, we first extracted knowledge from structured data and unstructured data. Since the extracted entities may contain some noise, we applied a biomedical information extraction system, named BioIE, to filter the data in KGHC. Then we introduced a fusion method which is used to fuse the extracted data. Finally, we stored the data into the Neo4j which can help researchers analyze the network of hepatocellular carcinoma.<bold>Results: </bold>KGHC contains 13,296 triples and provides the knowledge of hepatocellular carcinoma for healthcare professionals, making them free of digging into a large amount of biomedical literatures. This could hopefully improve the efficiency of researches on the hepatocellular carcinoma. KGHC is accessible free for academic research purpose at http://202.118.75.18:18895/browser/ .<bold>Conclusions: </bold>In this paper, we present a knowledge graph associated with hepatocellular carcinoma, which is constructed with vast amounts of structured and unstructured data. The evaluation results show that the data in KGHC is of high quality. [ABSTRACT FROM AUTHOR]
- Subjects :
- HEPATOCELLULAR carcinoma
MEDICAL personnel
DATA fusion (Statistics)
DATA mining
INFORMATION filtering systems
ARTERIAL catheters
INFORMATION storage & retrieval systems
MEDICAL informatics
RESEARCH
LIVER tumors
RESEARCH methodology
EVALUATION research
MEDICAL cooperation
COMPARATIVE studies
INFORMATION retrieval
INFORMATION science
Subjects
Details
- Language :
- English
- ISSN :
- 14726947
- Volume :
- 20
- Database :
- Complementary Index
- Journal :
- BMC Medical Informatics & Decision Making
- Publication Type :
- Academic Journal
- Accession number :
- 144473176
- Full Text :
- https://doi.org/10.1186/s12911-020-1112-5