Integrating multi-source data for skin burn classification using deep learning.

Journal: Computers in biology and medicine
Published Date: Jun 24, 2025

Abstract

BACKGROUND: Skin burns result from thermal or chemical damage to the skin, requiring timely and accurate assessment for effective treatment. Determining the degree of burns is crucial for appropriate clinical decisions, especially for interventions like grafting. However, visual burn degree classification is challenging for non-specialists, underscoring the need for Artificial Intelligence(AI)-powered tools to assist in burn assessment. Current AI models face challenges related to biases, validation, and limited data availability, and there is no standardized system for skin burn classification.

Authors

  • Ahmed Elsarta
    Department of Systems and Biomedical Engineering, Faculty of Engineering, Cairo University, Giza, Canada. Electronic address: ahmed.elsarta00@eng-st.cu.edu.eg.
  • Habiba Fathalla
    Department of Systems and Biomedical Engineering, Faculty of Engineering, Cairo University, Giza, Canada. Electronic address: habiba.elshenofy01@eng-st.cu.edu.eg.
  • Marina Nasser
    Department of Systems and Biomedical Engineering, Faculty of Engineering, Cairo University, Giza, Canada. Electronic address: marinanasser8@gmail.com.
  • Sara Elwatany
    Department of Systems and Biomedical Engineering, Faculty of Engineering, Cairo University, Giza, Canada. Electronic address: sara.abdullah00@eng-st.cu.edu.eg.
  • Rawan Fekry
    Department of Systems and Biomedical Engineering, Faculty of Engineering, Cairo University, Giza, Canada. Electronic address: rawanmohamedfekry@gmail.com.
  • Mohamed Ebaid
    Department of Plastic Surgery, Faculty of Medicine, Cairo University, Giza, Egypt. Electronic address: mohamed.ebaid@residents.kasralainy.du.eg.
  • Yomna Mahmoud
    Department of Plastic Surgery, Faculty of Medicine, Cairo University, Giza, Egypt. Electronic address: Yomna.s18893@gmail.com.
  • Ayman Anwar
  • Amira Gaber
    Systems and Biomedical Engineering Department, Faculty of Engineering, Cairo University, Giza, Egypt.

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