| Name: | Description: | Size: | Format: | |
|---|---|---|---|---|
| 249.8 KB | Adobe PDF |
Advisor(s)
Abstract(s)
Diabetes mellitus (DM) is a fast-growing metabolic condition that
threatens human population quality of living in the overcoming decades. One of
its severe consequences is diabetic foot ulcers (DFU), which affect up to a quarter
of the DM patients in their lifetime. This consequence leads to high health costs and
significant decrease of the patients’ quality of life and self-esteem. In order to cope
with the rising demands of heath resources and shortage in clinical human assets
intelligent computational tools are required to aid in the decision where a patient is
in an early stage of a DFU development and on the appraisal of a DFU treatment. It
is aim of this research to provide a critical overview of the existing decision support
systems (DSS) and publicly available research datasets for diabetic foot ulcers early
diagnosis and treatment assessment, and thus proposing a new infrastructure system
to deal with it overcoming the past attempts. The existing DFU DSS failed in being
introduced in clinical practice due to total discrepancy with current daily clinical
practice with DFU and the publicly available DM research datasets are shorter in
data for feeding a new DSS. This research presents the actual and promising future
data required for effective decisions and discloses a proposed architecture for a
DSS applicable to DFU early diagnosis and treatment evaluation. Implementing the
proposed system will take time but it will definitely contribute to cope with the patient
demands, associated cost reduction and promotion of patients care.
Description
Keywords
Big data Clinical datasets Decision support systems Diabetic foot ulcers Diagnostic tools Multiple data sources
