Towards an Effective Decision Support System for Diabetic Foot Ulcers Diagnostic and Treatment Assessment

• Autor(a) principal: Ricardo Vardasca, PhD, ASIS, FRPS
• Data de Publicação: 2022
• Outros Autores: Martinho, Domingos
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10400.26/43018
• topic: Big data; Clinical datasets; Decision support systems; Diabetic foot ulcers; Diagnostic tools; Multiple data sources; Treatment assessment

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.