Name
Title | ||
|---|---|---|
Investigating an ontology-based approach for Big Data analysis of inter-dependent medical and oral health conditions. |
Abstract | ||
|---|---|---|
The volume, velocity and variety of data generated today require special techniques and technologies for analysis and inferencing. These challenges are significantly pronounced within healthcare where data is being generated exponentially from biomedical research and electronic patient records. Moreover, with the increasing importance on holistic care, it has become vital to analyse information from all the domains that affect patient health, such as medical and oral conditions. A lot of medical and oral conditions are inter-dependent and call for collaborative management; however, technical issues such as heterogeneous data collection and storage formats, limited sharing of patient information, and lack of decision support over the shared information among others have seriously limited collaborative patient care. To address the above issues, the following research investigates the development and application of ontology and rules to build an evidence-based, reusable and cross-domain knowledge base. An example implementation of the knowledge base in Protégé is also done to evaluate the effectiveness of the approach for reasoning and decision support of cross-domain patient information. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1007/s10586-014-0406-8 | Cluster Computing |
Keywords | Field | DocType |
ontology,owl | Health care,Data science,Ontology,Data collection,Protégé,Computer science,Decision support system,Knowledge management,Patient care,Knowledge base,Big data | Journal |
Volume | Issue | ISSN |
18 | 1 | 1573-7543 |
Citations | PageRank | References |
13 | 0.70 | 39 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tejal Shah | 1 | 20 | 2.30 |
| Fethi Rabhi | 2 | 427 | 50.68 |
| Pradeep Ray | 3 | 123 | 9.12 |