Data Mining and Associated Analytical Tools as Decision Aids for Healthcare practitioners in Vascular Surgery
Mofidi, Reza (2018) Data Mining and Associated Analytical Tools as Decision Aids for Healthcare practitioners in Vascular Surgery. Doctoral thesis, University of Sunderland.
Item Type: | Thesis (Doctoral) |
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Abstract
Vascular surgery is an increasingly data rich speciality. Planning treatment and assessing outcomes are highly dependent on objective assessment of number of imaging modalities including duplex ultrasound, CT scans and angiograms which are almost exclusively digitally created stored and accessed. Developments such as the national vascular registry mean that treatment outcomes are recorded scrutinised electronically. The widespread availability of data which is collected electronically and stored for future clinical use has created the opportunity to examine the efficacy of investigations and treatments in a way which has hitherto not been possible. In addition, new computational methods for data analysis have provided the opportunity for the clinicians and researchers to utilise this data to address pertinent clinical questions.
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Depositing User: Barry Hall |
Identifiers
Item ID: 9553 |
URI: http://sure.sunderland.ac.uk/id/eprint/9553 |
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Catalogue record
Date Deposited: 18 May 2018 10:08 |
Last Modified: 20 May 2019 11:18 |
Author: | Reza Mofidi |
University Divisions
Faculty of Health Sciences and WellbeingSubjects
Sciences > Health SciencesActions (login required)
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