Machine and deep learning methods in identifying malaria through microscopic blood smear : A systematic review

• 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: Elsevier B.V. 2024
• Subjects: Q Science (General); TA Engineering (General). Civil engineering (General)
• Online Access: http://ir.unimas.my/id/eprint/44687/3/Machine.pdf; http://ir.unimas.my/id/eprint/44687/; https://www.sciencedirect.com/science/article/abs/pii/S0952197624006870; https://doi.org/10.1016/j.engappai.2024.108529

Despite the persistency of World Health Organization to eliminate malaria since 1987, malaria disease continues to pose a significant threat to global health. As the severity of malaria persists over the years, there is a critical need for an automated diagnosis system for more efficient diagnosis a...