Improving Malaria diagnosis through interpretable customized CNNs architectures

Ahamed, Md. FaysalNahiduzzaman, Md.Mahmud, GolamShafi, Fariya BintayAyari, Mohamed ArseleneKhandakar, AmithAbdullah-Al-Wadud, M.Islam, S. M. Riazul2025-04-232025-04-232025-02-25Ahamed, M F, Nahiduzzaman, M, Mahmud, G, Shafi, F B, Ayari, M A, Khandakar, A, Abdullah-Al-Wadud, M & Islam, S M R 2025, 'Improving Malaria diagnosis through interpretable customized CNNs architectures', Scientific Reports, vol. 15, 6484. https://doi.org/10.1038/s41598-025-90851-12045-2322ORCID: /0000-0003-2968-9561/work/183073390https://hdl.handle.net/2164/25358358842912engSDG 3 - Good Health and Well-beingParallel convolutional neural network (PCNN)Soft AttentionBlood smearPlasmodium parasiteMalariaDiagnosisR Medicine (General)Supplementary DataDASLinkhttps://lhncbc.nlm.nih.gov/LHC-research/LHC-projects/image-processing/malaria-datasheet.htmlR1Improving Malaria diagnosis through interpretable customized CNNs architecturesJournal article10.1038/s41598-025-90851-115