An automated neural network-based stage-specific malaria detection software using dimension reduction: The malaria microscopy classifier.

ABSTRACT: Due to climate change and the COVID-19 pandemic, the number of malaria cases and deaths, caused by the Plasmodium genus, of which P. falciparum is the most common and lethal to humans, increased between 2019 and 2020. Reversing this trend and eliminating malaria worldwide requires improvements in malaria diagnosis, in which artificial intelligence (AI) has recently been demonstrated to have a great potential. One of the main reasons for the use of neural networks (NNs) is the time saving through automatising the process and the elimination of human error. When classifying with two-dimensional images of red blood cells (RBCs), the number of parameters fitted by the NN for the classification of RBCs is extremely high, which strongly influences the performance of the network, es

SUBMITTER: Katharina P 

PROVIDER: S-EPMC10165163 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature