Use this URL to cite or link to this record in EThOS: | https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.742083 |
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Title: | Data mining and associated analytical tools as decision aids for healthcare practitioners in vascular surgery | ||||||
Author: | Mofidi, Reza |
ISNI:
0000 0004 7226 497X
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Awarding Body: | University of Sunderland | ||||||
Current Institution: | University of Sunderland | ||||||
Date of Award: | 2018 | ||||||
Availability of Full Text: |
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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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Supervisor: | Not available | Sponsor: | Not available | ||||
Qualification Name: | Thesis (Ph.D.) | Qualification Level: | Doctoral | ||||
EThOS ID: | uk.bl.ethos.742083 | DOI: | Not available | ||||
Keywords: | Health Sciences | ||||||
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