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Diabetic Foot Ulcer (DFU) is a complication of diabetes and is characterized by wounds associated with ischemia, neuropathy and deformities which can lead to amputation. The symptomatology of DFU is so characteristic for this disease, what could be used for the development of diagnosis tool. This work details the design of a software (Claucia) based on the study of clinical images by Machine Learning and Artificial Intelligence (AI), for the diagnosis of DUF, with the outcome of a pattern registration with number code BR512022001637. The sample universe consisted of 554 UPD records obtained in the clinical trial of the RAPHA® project. The tool interface and commands were designed to make it user-friendly for professionals with no programming background.

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Machine Learning to Automate Classification of Diabetic Foot Ulcer (DFU) Photographic Records According to the University of Texas Classification

  • 会议论文

  • 发表日期：

    2025年

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  • L. M. Syllos,
  • T. Alves-Espindola,
  • S. S. R. Fleury-Rosa,
  • M. L. Brettas-Carneiro

摘要

Diabetic Foot Ulcer (DFU) is a complication of diabetes and is characterized by wounds associated with ischemia, neuropathy and deformities which can lead to amputation. The symptomatology of DFU is so characteristic for this disease, what could be used for the development of diagnosis tool. This work details the design of a software (Claucia) based on the study of clinical images by Machine Learning and Artificial Intelligence (AI), for the diagnosis of DUF, with the outcome of a pattern registration with number code BR512022001637. The sample universe consisted of 554 UPD records obtained in the clinical trial of the RAPHA® project. The tool interface and commands were designed to make it user-friendly for professionals with no programming background.