Name
Title | ||
|---|---|---|
Automated domain-specific healthcare knowledge graph curation framework: Subarachnoid hemorrhage as phenotype. |
Abstract | ||
|---|---|---|
•A novel automated domain-specific knowledge graph curation framework.•First attempt towards knowledge graph construction for subarachnoid hemorrhage stroke.•Enables extraction of concepts, relations, individual & cohort graphs, and predictive knowledge.•Uses ontology-based information extraction, ensemble learning and relation embedding techniques.•Competitive results in most of the tasks of knowledge graph generation. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.eswa.2019.113120 | Expert Systems with Applications |
Keywords | Field | DocType |
Knowledge Graph,Ontology,Electronic Health Records,Intracranial Aneurysm,Association Rules,Ensemble Learning,Subarachnoid Hemorrhage Stroke | Ontology,Computer science,Precision and recall,Unstructured data,Information extraction,Natural language processing,Artificial intelligence,Clinical decision support system,Word embedding,Ensemble learning,Recall,Machine learning | Journal |
Volume | ISSN | Citations |
145 | 0957-4174 | 1 |
PageRank | References | Authors |
0.34 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Khalid Mahmood Malik | 1 | 26 | 9.32 |
| Madan Krishnamurthy | 2 | 3 | 1.84 |
| Mazen Alobaidi | 3 | 20 | 3.96 |
| Maqbool Hussain | 4 | 197 | 20.21 |
| Fakhare Alam | 5 | 1 | 0.34 |
| Ghaus M. Malik | 6 | 2 | 2.08 |