An optimised YOLOv4 deep learning model for efficient malarial cell detection in thin blood smear images

• Main Authors: Dhevisha, Sukumarran, Khairunnisa, Hasikin, Anis Salwa, Mohd Khairuddin, Romano, Ngui, Wan Yusoff, Wan Sulaiman, Indra, Vythilingam, Paul Cliff, Simon Divis
• Format: Article
• Language: English
• Published: BioMed Central Ltd. 2024
• Subjects: RZ Other systems of medicine
• Online Access: http://ir.unimas.my/id/eprint/44586/1/2024_Sukumarran%20et%20al_AI%20Malaria%20Detection.pdf; http://ir.unimas.my/id/eprint/44586/; https://parasitesandvectors.biomedcentral.com/articles/10.1186/s13071-024-06215-7; https://doi.org/10.1186/s13071-024-06215-7
• Institution: Universiti Malaysia Sarawak

Background Malaria is a serious public health concern worldwide. Early and accurate diagnosis is essential for controlling the disease’s spread and avoiding severe health complications. Manual examination of blood smear samples by skilled technicians is a time-consuming aspect of the conventional m...