Adeel Akram¹, Tallha Akram², Ghada Atteia^3,*, Ayman Qahmash⁴, Sultan Alanazi⁵, Faisal Mohammad Alotaibi⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.2, pp. 2311-2337, 2025, DOI:10.32604/cmes.2025.069697 - 26 November 2025

Abstract Advancements in radiation-based imaging and computational intelligence have significantly improved medical diagnostics, particularly in dermatology. This study presents an ensemble-based skin lesion classification framework that integrates deep neural networks (DNNs) with transfer learning, a customized DNN, and an optimized self-learning binary differential evolution (SLBDE) algorithm for feature selection and fusion. Leveraging computational techniques alongside medical imaging modalities, the proposed framework extracts and fuses discriminative features from multiple pre-trained models to improve classification robustness. The methodology is evaluated on benchmark datasets, including ISIC 2017 and the Argentina Skin Lesion dataset, demonstrating superior accuracy, precision, and F1-score… More >

Rafid Sagban^1,2,*, Haydar Abdulameer Marhoon^3,4, Saadaldeen Rashid Ahmed^5,6,*

Intelligent Automation & Soft Computing, Vol.39, No.6, pp. 1035-1051, 2024, DOI:10.32604/iasc.2024.058416 - 30 December 2024

Abstract Skin cancer is a highly frequent kind of cancer. Early identification of a phenomenon significantly improves outcomes and mitigates the risk of fatalities. Melanoma, basal, and squamous cell carcinomas are well-recognized cutaneous malignancies. Malignant We can differentiate Melanoma from non-pigmented carcinomas like basal and squamous cell carcinoma. The research on developing automated skin cancer detection systems has primarily focused on pigmented malignant type melanoma. The limited availability of datasets with a wide range of lesion categories has hindered in-depth exploration of non-pigmented malignant skin lesions. The present study investigates the feasibility of automated methods for… More >

TRINIDAD MONTERO-VILCHEZ^1,2,*, MANUEL SANCHEZ-DIAZ^1,2, CAROLINA MONTERO-VILCHEZ³, ALVARO SIERRA-SANCHEZ², SALVADOR ARIAS-SANTIAGO^1,2,4

BIOCELL, Vol.46, No.11, pp. 2363-2367, 2022, DOI:10.32604/biocell.2022.021399 - 07 July 2022

Abstract Atopic dermatitis (AD) is a chronic cutaneous inflammatory disease caused by an interaction between genetic, immune and epidermal barrier factors. Several treatments can be used to treat this disease but there are patients that do not respond to actual drugs. So, there is a need to develop effective therapies for AD. Mesenchymal stem cells (MSCs) are non-hematopoietic multipotent adult progenitor cells with immunomodulatory power and self-regenerating capacity to repair tissue damage, so they could be a potential effective treatment for AD. MSCs-Conditioned Medium (CM) and MSCs-exosomes are cell-free preparation with molecules secreted by stem cells More >