{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T16:45:31Z","timestamp":1776357931371,"version":"3.51.2"},"reference-count":52,"publisher":"Tech Science Press","issue":"3","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["CMC"],"published-print":{"date-parts":[[2025]]},"DOI":"10.32604\/cmc.2025.063851","type":"journal-article","created":{"date-parts":[[2025,4,18]],"date-time":"2025-04-18T04:28:45Z","timestamp":1744950525000},"page":"5299-5321","source":"Crossref","is-referenced-by-count":1,"title":["A Multi-Layers Information Fused Deep Architecture for Skin Cancer Classification in Smart Healthcare"],"prefix":"10.32604","volume":"83","author":[{"given":"Veena","family":"Dillshad","sequence":"first","affiliation":[]},{"given":"Muhammad Attique","family":"Khan","sequence":"additional","affiliation":[]},{"given":"Muhammad","family":"Nazir","sequence":"additional","affiliation":[]},{"given":"Jawad","family":"Ahmad","sequence":"additional","affiliation":[]},{"given":"Dina Abdulaziz","family":"AlHammadi","sequence":"additional","affiliation":[]},{"given":"Taha","family":"Houda","sequence":"additional","affiliation":[]},{"given":"Hee-Chan","family":"Cho","sequence":"additional","affiliation":[]},{"given":"Byoungchol","family":"Chang","sequence":"additional","affiliation":[]}],"member":"17807","published-online":{"date-parts":[[2025]]},"reference":[{"key":"ref1","doi-asserted-by":"crossref","first-page":"1120","DOI":"10.3390\/cancers16061120","article-title":"Improving skin Lesion segmentation with self-training","volume":"16","author":"Dzieniszewska","year":"2024","journal-title":"Cancers"},{"key":"ref2","doi-asserted-by":"crossref","first-page":"123056","DOI":"10.1016\/j.eswa.2023.123056","article-title":"A novel end-to-end deep convolutional neural network based skin lesion classification framework","volume":"246","author":"Sulthana","year":"2024","journal-title":"Expert Syst Appl"},{"key":"ref3","doi-asserted-by":"crossref","first-page":"1088","DOI":"10.1111\/jdv.18050","article-title":"Prevalence of most common skin diseases in Europe: a population-based study","volume":"36","author":"Richard","year":"2022","journal-title":"J Eur Acad Dermatol Venereol"},{"key":"ref4","doi-asserted-by":"crossref","first-page":"108303","DOI":"10.1016\/j.compbiomed.2024.108303","article-title":"LSCS-Net: a lightweight skin cancer segmentation network with densely connected multi-rate atrous convolution","volume":"11","author":"Din","year":"2024","journal-title":"Comput Biol Med"},{"key":"ref5","doi-asserted-by":"crossref","first-page":"553","DOI":"10.1001\/jamadermatol.2020.0470","article-title":"Evaluation of sex-specific incidence of melanoma","volume":"156","author":"Olsen","year":"2020","journal-title":"JAMA Dermatol"},{"key":"ref6","doi-asserted-by":"crossref","first-page":"98","DOI":"10.1097\/CCO.0000000000000611","article-title":"Use of noninvasive imaging in the management of skin cancer","volume":"32","author":"Giuffrida","year":"2020","journal-title":"Curr Opin Oncol"},{"key":"ref7","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1016\/S1470-2045(02)00679-4","article-title":"Diagnostic accuracy of dermoscopy","volume":"3","author":"Kittler","year":"2002","journal-title":"Lancet Oncol"},{"key":"ref8","doi-asserted-by":"crossref","first-page":"712","DOI":"10.1111\/j.1365-4632.2008.03556.x","article-title":"Dermoscopy: basic concepts","volume":"47","author":"Campos-do-Carmo","year":"2008","journal-title":"Int J Dermatol"},{"key":"ref9","doi-asserted-by":"crossref","first-page":"114204","DOI":"10.1016\/j.eswa.2020.114204","article-title":"Dermatological expert system implementing the ABCD rule of dermoscopy for skin disease identification","volume":"167","author":"Chatterjee","year":"2021","journal-title":"Expert Syst Appl"},{"key":"ref10","doi-asserted-by":"crossref","first-page":"1445318","DOI":"10.3389\/fmed.2024.1445318","article-title":"Integrating generative AI with ABCDE rule analysis for enhanced skin cancer diagnosis, dermatologist training and patient education","volume":"11","author":"J\u00fctte","year":"2024","journal-title":"Front Med"},{"key":"ref11","doi-asserted-by":"crossref","first-page":"106624","DOI":"10.1016\/j.compbiomed.2023.106624","article-title":"A survey, review, and future trends of skin lesion segmentation and classification","volume":"155","author":"Hasan","year":"2023","journal-title":"Comput Biol Med"},{"key":"ref12","doi-asserted-by":"crossref","first-page":"107988","DOI":"10.1016\/j.compbiomed.2024.107988","article-title":"SG-MIAN: self-guided multiple information aggregation network for image-level weakly supervised skin lesion segmentation","volume":"170","author":"Li","year":"2024","journal-title":"Comput Biol Med"},{"key":"ref13","first-page":"15","article-title":"Comparative analysis of machine learning models for automated skin cancer detection: advancements in diagnostic accuracy and AI integration","volume":"7","author":"Nguyen","year":"2025","journal-title":"Am J Medical Sci Pharm Res"},{"key":"ref14","doi-asserted-by":"crossref","first-page":"106084","DOI":"10.1016\/j.bspc.2024.106084","article-title":"A novel Deeplabv3+ and vision-based transformer model for segmentation and classification of skin lesions","volume":"92","author":"Ahmad","year":"2024","journal-title":"Biomed Signal Process Control"},{"key":"ref15","doi-asserted-by":"crossref","first-page":"18907","DOI":"10.1007\/s11042-023-16255-3","article-title":"Bootstrapping of fine-tuned segmentation and classification network for epidermis disorder categorization","volume":"83","author":"Kalaivani","year":"2024","journal-title":"Multimed Tools Appl"},{"key":"ref16","doi-asserted-by":"crossref","first-page":"108798","DOI":"10.1016\/j.compbiomed.2024.108798","article-title":"Skin-CAD: explainable deep learning classification of skin cancer from dermoscopic images by feature selection of dual high-level CNNs features and transfer learning","volume":"178","author":"Attallah","year":"2024","journal-title":"Comput Biol Med"},{"key":"ref17","doi-asserted-by":"crossref","first-page":"100357","DOI":"10.1016\/j.array.2024.100357","article-title":"Advances of AI in image-based computer-aided diagnosis: a review","volume":"23","author":"Yeasmin","year":"2024","journal-title":"Array"},{"key":"ref18","doi-asserted-by":"crossref","first-page":"5757","DOI":"10.1007\/s00521-023-09366-3","article-title":"The deep learning applications in IoT-based bio-and medical informatics: a systematic literature review","volume":"36","author":"Amiri","year":"2024","journal-title":"Neural Comput Appl"},{"key":"ref19","doi-asserted-by":"crossref","first-page":"e8091","DOI":"10.1002\/cpe.8091","article-title":"A new service composition method in the cloud-based internet of things environment using a grey wolf optimization algorithm and MapReduce framework","volume":"36","author":"Vakili","year":"2024","journal-title":"Concurr Comput"},{"key":"ref20","doi-asserted-by":"crossref","first-page":"107627","DOI":"10.1016\/j.bspc.2025.107627","article-title":"A novel CNN-ViT-based deep learning model for early skin cancer diagnosis","volume":"104","author":"Pacal","year":"2025","journal-title":"Biomed Signal Process Control"},{"key":"ref21","doi-asserted-by":"crossref","first-page":"106321","DOI":"10.1016\/j.compbiomed.2022.106321","article-title":"Learning from dermoscopic images in association with clinical metadata for skin lesion segmentation and classification","volume":"152","author":"Dong","year":"2023","journal-title":"Comput Biol Med"},{"key":"ref22","doi-asserted-by":"crossref","first-page":"4938","DOI":"10.1038\/s41598-025-89230-7","article-title":"A robust deep learning framework for multiclass skin cancer classification","volume":"15","author":"Ozdemir","year":"2025","journal-title":"Sci Rep"},{"key":"ref23","doi-asserted-by":"crossref","first-page":"128962","DOI":"10.1016\/j.neucom.2024.128962","article-title":"The impact of multiclass information decoupling in latent space on skin lesion segmentation","volume":"617","author":"Zhang","year":"2025","journal-title":"Neurocomputing"},{"key":"ref24","doi-asserted-by":"crossref","first-page":"e12497","DOI":"10.1111\/exsy.12497","article-title":"Skin lesion segmentation and classification: a unified framework of deep neural network features fusion and selection","volume":"39","author":"Khan","year":"2022","journal-title":"Expert Syst"},{"key":"ref25","doi-asserted-by":"crossref","first-page":"1143","DOI":"10.1002\/ima.22699","article-title":"Skin lesion segmentation using an improved framework of encoder-decoder based convolutional neural network","volume":"32","author":"Kaur","year":"2022","journal-title":"Int J Imaging Syst Technol"},{"key":"ref26","doi-asserted-by":"crossref","first-page":"119230","DOI":"10.1016\/j.eswa.2022.119230","article-title":"Fusion of U-Net and CNN model for segmentation and classification of skin lesion from dermoscopy images","volume":"213","author":"Anand","year":"2023","journal-title":"Expert Syst Appl"},{"key":"ref27","doi-asserted-by":"crossref","first-page":"53875","DOI":"10.1007\/s11042-023-17042-w","article-title":"An optimized boosting framework for skin lesion segmentation and classification","volume":"83","author":"Yadav","year":"2023","journal-title":"Multimed Tools Appl"},{"key":"ref28","doi-asserted-by":"crossref","first-page":"912","DOI":"10.3390\/diagnostics13050912","article-title":"A collaborative learning model for skin lesion segmentation and classification","volume":"13","author":"Wang","year":"2023","journal-title":"Diagnostics"},{"key":"ref29","doi-asserted-by":"crossref","first-page":"111624","DOI":"10.1016\/j.asoc.2024.111624","article-title":"Explainable deep inherent learning for multi-classes skin lesion classification","volume":"159","author":"Hosny","year":"2024","journal-title":"Appl Soft Comput"},{"key":"ref30","doi-asserted-by":"crossref","first-page":"16498","DOI":"10.1109\/ACCESS.2024.3360215","article-title":"A GAN-based data augmentation method for imbalanced multiclass skin lesion classification","volume":"12","author":"Su","year":"2024","journal-title":"IEEE Access"},{"key":"ref31","doi-asserted-by":"crossref","first-page":"238","DOI":"10.1016\/j.neunet.2023.01.022","article-title":"Multiclass skin lesion localization and classification using deep learning based features fusion and selection framework for smart healthcare","volume":"160","author":"Maqsood","year":"2023","journal-title":"Neural Netw"},{"key":"ref32","doi-asserted-by":"crossref","first-page":"101701","DOI":"10.1016\/j.tice.2021.101701","article-title":"Multi-features extraction based on deep learning for skin lesion classification","volume":"74","author":"Benyahia","year":"2022","journal-title":"Tissue Cell"},{"key":"ref33","doi-asserted-by":"crossref","first-page":"6713","DOI":"10.1007\/s00521-022-08053-z","article-title":"Multiclass skin lesion classification in dermoscopic images using swin transformer model","volume":"35","author":"Ayas","year":"2023","journal-title":"Neural Comput Appl"},{"key":"ref34","doi-asserted-by":"crossref","first-page":"364","DOI":"10.3390\/math11020364","article-title":"DeepLabv3+-based segmentation and best features selection using slime mould algorithm for multiclass skin lesion classification","volume":"11","author":"Zafar","year":"2023","journal-title":"Mathematics"},{"key":"ref35","doi-asserted-by":"crossref","first-page":"3063","DOI":"10.3390\/diagnostics13193063","article-title":"MSRNet: multiclass skin lesion recognition using additional residual block based fine-tuned deep models information fusion and best feature selection","volume":"13","author":"Bibi","year":"2023","journal-title":"Diagnostics"},{"key":"ref36","doi-asserted-by":"crossref","first-page":"34885","DOI":"10.1007\/s11042-023-14892-2","article-title":"An automated multiclass skin lesion diagnosis by embedding local and global features of Dermoscopy images","volume":"82","author":"Kadirappa","year":"2023","journal-title":"Multimed Tools Appl"},{"key":"ref37","doi-asserted-by":"crossref","first-page":"207","DOI":"10.1049\/cit2.12267","article-title":"D2LFS2Net: multiclass skin lesion diagnosis using deep learning and variance-controlled Marine Predator optimisation: an application for precision medicine","volume":"10","author":"Dillshad","year":"2025","journal-title":"CAAI Trans Intell Technol"},{"key":"ref38","doi-asserted-by":"crossref","first-page":"e1520","DOI":"10.7717\/peerj-cs.1520","article-title":"MSCDNet-based multiclass classification of skin cancer using dermoscopy images","volume":"9","author":"Radhika","year":"2023","journal-title":"PeerJ Comput Sci"},{"key":"ref39","doi-asserted-by":"crossref","first-page":"385","DOI":"10.3390\/diagnostics13030385","article-title":"Light-Dermo: a lightweight pretrained convolution neural network for the diagnosis of multiclass skin lesions","volume":"13","author":"Baig","year":"2023","journal-title":"Diagnostics"},{"key":"ref40","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1186\/s40537-023-00769-6","article-title":"Skin-Net: a novel deep residual network for skin lesions classification using multilevel feature extraction and cross-channel correlation with detection of outlier","volume":"10","author":"Alsahafi","year":"2023","journal-title":"J Big Data"},{"key":"ref41","doi-asserted-by":"crossref","first-page":"638","DOI":"10.3390\/biomedinformatics4010035","article-title":"Naturalize revolution: unprecedented AI-Driven precision in skin cancer classification using deep learning","volume":"4","author":"Abou Ali","year":"2024","journal-title":"BioMedInformatics"},{"key":"ref42","doi-asserted-by":"crossref","first-page":"111794","DOI":"10.1016\/j.asoc.2024.111794","article-title":"A lightweight deep convolutional neural network model for skin cancer image classification","volume":"162","author":"Tuncer","year":"2024","journal-title":"Appl Soft Comput"},{"key":"ref43","doi-asserted-by":"crossref","first-page":"201","DOI":"10.1186\/s12880-024-01356-8","article-title":"Enhanced skin cancer diagnosis using optimized CNN architecture and checkpoints for automated dermatological lesion classification","volume":"24","author":"Musthafa","year":"2024","journal-title":"BMC Med Imaging"},{"key":"ref44","doi-asserted-by":"crossref","first-page":"180161","DOI":"10.1038\/sdata.2018.161","article-title":"The HAM10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions","volume":"5","author":"Tschandl","year":"2018","journal-title":"Sci Data"},{"key":"ref45","doi-asserted-by":"crossref","first-page":"114822","DOI":"10.1109\/ACCESS.2020.3003890","article-title":"Skin lesions classification into eight classes for ISIC, 2019 using deep convolutional neural network and transfer learning","volume":"8","author":"Kassem","year":"2020","journal-title":"IEEE Access"},{"key":"ref46","doi-asserted-by":"crossref","first-page":"1153","DOI":"10.1016\/j.asoc.2018.02.053","article-title":"Information entropy based sample reduction for support vector data description","volume":"71","author":"Li","year":"2018","journal-title":"Appl Soft Comput"},{"key":"ref47","doi-asserted-by":"crossref","first-page":"2677","DOI":"10.3390\/app12052677","article-title":"Multiclass skin lesion classification using a novel lightweight deep learning framework for smart healthcare","volume":"12","author":"Hoang","year":"2022","journal-title":"Appl Sci"},{"key":"ref48","doi-asserted-by":"crossref","first-page":"4399","DOI":"10.3390\/s22124399","article-title":"Skin lesion classification using collective intelligence of multiple neural networks","volume":"22","author":"Popescu","year":"2022","journal-title":"Sensors"},{"key":"ref49","series-title":"2022 Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT)","first-page":"506","article-title":"Multiclass skin lesion classification using densenet","author":"Neeshma","year":"2022"},{"key":"ref50","series-title":"IEEE 2nd Mysore Sub Section International Conference (MysuruCon)","first-page":"1","article-title":"Multiclass classification of skin cancer using convolutional neural network","author":"Shobha","year":"2022"},{"key":"ref51","series-title":"Proceedings of KIIT Conference","first-page":"1142","article-title":"Performance comparison of deep learning models for skin disease classification using the HAM10000 dataset","author":"Jaehyo","year":"2024"},{"key":"ref52","first-page":"1","article-title":"Early-stage melanoma cancer diagnosis framework for imbalanced data from dermoscopic images","volume":"8","author":"Khan","year":"2024","journal-title":"Microsc Res Tech"}],"container-title":["Computers, Materials & Continua"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/cdn.techscience.cn\/files\/cmc\/2025\/TSP_CMC-83-3\/TSP_CMC_63851\/TSP_CMC_63851.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,17]],"date-time":"2025-11-17T01:31:22Z","timestamp":1763343082000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.techscience.com\/cmc\/v83n3\/61061"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":52,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2025]]},"published-print":{"date-parts":[[2025]]}},"URL":"https:\/\/doi.org\/10.32604\/cmc.2025.063851","relation":{},"ISSN":["1546-2226"],"issn-type":[{"value":"1546-2226","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]}}}