Extracting Health Ontology Schema from a PDF File
| dc.contributor.advisor | Eric Atwell | |
| dc.contributor.author | MOHAMMED NIDAA ALHARBI | |
| dc.date | 2021 | |
| dc.date.accessioned | 2022-05-26T16:49:48Z | |
| dc.date.available | 2022-05-26T16:49:48Z | |
| dc.degree.department | School of Computing | |
| dc.degree.grantor | University of Leeds - School of Computing | |
| dc.description.abstract | The goal of the healthcare provider has always been to examine a patient’s symptoms in order to diagnose medical issues and make an informed decision in order to cure the patient. Over the years, medial practises have been improved upon to include additional data, involving socioeconomics, demographics, and family history in clinical decision-making processes. Therefore, the healthcare system is oversupplied with data. Since health data is the fuel of health research, high-quality health data needs to be accessible to health providers in a standardised way. the goal of this master project is to extract an ontology from a PDF file of health dictionary | |
| dc.identifier.uri | https://drepo.sdl.edu.sa/handle/20.500.14154/30446 | |
| dc.language.iso | en | |
| dc.title | Extracting Health Ontology Schema from a PDF File | |
| sdl.thesis.level | Master | |
| sdl.thesis.source | SACM - United Kingdom |