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Towards accurate diabetic foot ulcers quantification using novel multimodal dataset


   Applied Computational Science

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  Prof M Yap  No more applications being accepted  Funded PhD Project (UK Students Only)

About the Project

Wound care places a significant burden on the NHS. Currently ~2.2 million patients have chronic wounds, costing the NHS £5.3 billions per year for managing wounds and their associated comorbidities/amputations.

An accurate and automated computerised solution to measure and characterise the wound area would be greatly beneficial for remote assessment and monitoring, but it does not exist. This project will develop an innovative digital technology solution to increase the confidence of clinicians in monitoring the wounds. In addition, it will increase the trust of end-users in digital technology and provide more accurate and improved care for patients. The proposed system will help to promote early intervention, a key facet in reducing healthcare costs, by encouraging patients to monitor their condition.  

The successful candidate will be based within our Centre for Advanced Computational Science research centre (CfACS).

Aims and objectives

This project aims to design innovative multimodal intelligent techniques to enable accurate measurement of diabetic foot ulcers and wounds. The research objectives are to:  

  1. Create a world-leading multi-modal digital wound repository  
  2. Design an innovative modelling tool for wound assessment 
  3. Create a novel algorithm using multimodal dataset to improve the accuracy of predicting ulcer/wound healing 

For more information visit https://www.mmu.ac.uk/research/research-study/scholarships#ai-71374-6


Funding Notes

Fully-funded PhD (home fees), stipend paid at 2022/23 rate of £16,062. Expected start date January 2023.

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Research output data provided by the Research Excellence Framework (REF)

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