Sökning: onr:"swepub:oai:DiVA.org:lnu-131822" >
A novel link predic...
A novel link prediction approach on clinical knowledge graphs utilizing graph structures
-
- Dörpinghaus, Jens (författare)
- Federal Institute for Vocational Education and Training (BIBB), Germany; German Center for Neurodegenerative Diseases (DZNE), Germany
-
- Hübenthal, Tobias (författare)
- University of Cologne, Germany
-
- Faber, Jennifer (författare)
- German Center for Neurodegenerative Diseases (DZNE), Germany
-
(creator_code:org_t)
- 2022-09-26
- 2022
- Engelska.
-
Ingår i: Proceedings of the of the 17th Conference on ComputerScience and Intelligence Systems. - : Polish information processing society (PTI). - 9788396242396 - 9788396589705 - 9788396589712 ; , s. 43-52
- Relaterad länk:
-
https://doi.org/10.1...
-
visa fler...
-
https://lnu.diva-por... (primary) (Raw object)
-
https://urn.kb.se/re...
-
https://doi.org/10.1...
-
visa färre...
Abstract
Ämnesord
Stäng
- This paper presents a novel approach towards link prediction in clinical knowledge graphs. They play a central role in linking data from different data sources and are widely used in big data integration, especially for connecting data from different domains. We present a knowledge graph initially built on data from a clinical trial on Spinocerebellar ataxia type 3 (SCA3), which is a rare autosomal dominant inherited disorder. The contributions of this paper are (1) to create a feasible data representation schema capable of handling clinical imaging data in a knowledge graph and to (2) convert the data efficiently into a knowledge graph. Due to the limited amount of patient-nodes usually common methods for link prediction and graph embeddings are problematic and thus we will (3) present a novel approach for link prediction utilising graph structures and Conditional Random Fields. In addition, we present (4) an extensive evaluation underlining the importance of (a) data management and (b) further research on link prediction using graph structures.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap -- Systemvetenskap, informationssystem och informatik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Information Systems (hsv//eng)
Nyckelord
- Informatik
- Information Systems
Publikations- och innehållstyp
- ref (ämneskategori)
- kon (ämneskategori)
Hitta via bibliotek
Till lärosätets databas