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.

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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.

Item Type: Thesis (Doctoral)
Subjects: Sciences > Health Sciences
Divisions: Faculty of Health Sciences and Wellbeing
Depositing User: Barry Hall
Date Deposited: 18 May 2018 10:08
Last Modified: 18 May 2018 10:08
URI: http://sure.sunderland.ac.uk/id/eprint/9553

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