Optimizing Skin Disease Diagnosis using Metaheuristic Algorithms: A Comparative Study

Authors

  • Israa Alsaadi University of Baghdad Author
  • Nuha Salim Mohammed University of Diyala Author
  • Saja Salim Mohammed University of Diyala Author

DOI:

https://doi.org/10.69923/IJAS.2024.010108

Keywords:

Skin Disease , Comparative Study, Optimizing , Metaheuristic Algorithms

Abstract

Skin disease, having a wide range of symptoms and appearances, has been putting stern challenge in the field of dermatology. In deep demand, the work reveals the potential of metaheuristic algorithms for skin disease diagnosis and aims a comparison with traditional diagnostic techniques. For the study, a real-time dataset is collected including clinical information, medical images and histopathological data of several patients affected with different skin diseases. The test dataset is reviewed to ensure its perfection and representation among several categories of diseases. Several metaheuristic algorithms are introduced like particle swarm optimization (PSO), genetic algorithm (GA), antlion optimization (ALO) and ant colony optimization (ACO) in the study. To examine the performance of the proposed metaheuristic algorithms, a comparative analysis is conducted. Furthermore, certain performance metrics such as diagnostic accuracy and results of standard deviation, mean fitness score, best fitness score, and worst fitness score are calculated. The results of our comparative analysis also indicate variations in selecting different metaheuristic algorithms. Therefore, our evaluation presents the significance of selecting the suitable algorithm for medical diagnosis based on the requirements of the clinical data and disease type.

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Author Biographies

  • Israa Alsaadi, University of Baghdad

    Israa Alsaadi is an assistant lecturer at College of Science for women, University of Baghdad, Iraq. She received her B.Sc. degree in Computer Science from the University of Technology in Iraq, Baghdad. She obtained her M.Sc. degree from the University of Bedfordshire in the in United Kingdom. Her research areas are AI, Machine Learning, Big data, Images Processing, and Images Analysis and Pattern Recognition. She has published several scientific papers in national, international conferences and journals

  • Nuha Salim Mohammed , University of Diyala

    Nuha Salim Mohammed is an assistant lecturer at the College of Science, University of Diyala, and Middle Technical University, Iraq. She received the B.Sc. and M.Sc. degrees in computer science from the University of Diyala , Iraq. with specialization in security and AI. Her research areas are Data Security , Image Processing, AI, Image Analysis and Pattern Recognition. She published several scientific papers in both national and international conferences and journals

  • Saja Salim Mohammed , University of Diyala

    Saja Salim Mohammed is an assistant lecturer at the University of Diyala since 2021. She obtained her M.Sc. in computer science from the University of Diyala College of Sciences, Diyala, Iraq. Her thesis is titled “Skin Disease Classification Approach Based on Metaheuristic Optimization.”. In addition, she works at the Faculty of Physical Education and Sports Sciences at the University of Diyala. Her research interests are Neural Networks, Pattern Recognition, the Internet of Things, Cloud Computing, and Metaheuristic Algorithms

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Published

06/30/2024

Issue

Section

Articles

How to Cite

[1]
“Optimizing Skin Disease Diagnosis using Metaheuristic Algorithms: A Comparative Study”, IJApSc, vol. 1, no. 1, pp. 72–80, Jun. 2024, doi: 10.69923/IJAS.2024.010108.

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