Research Article
A Review of Computer-Assisted Techniques Performances in Malaria Diagnosis
@INPROCEEDINGS{10.1007/978-3-031-33545-7_1, author={Ibrahim Mouazamou Laoualy Chaharou and Jules Degila and Lawani Isma\~{n}l and Habiboulaye Amadou Boubacar}, title={A Review of Computer-Assisted Techniques Performances in Malaria Diagnosis}, proceedings={IoT and Big Data Technologies for Health Care. Third EAI International Conference, IoTCare 2022, Virtual Event, December 12-13, 2022, Proceedings}, proceedings_a={IOTCARE}, year={2023}, month={5}, keywords={Malaria Diagnosis Machine learning Computer-assisted techniques Performance metrics Deep learning}, doi={10.1007/978-3-031-33545-7_1} }- Ibrahim Mouazamou Laoualy Chaharou
Jules Degila
Lawani Ismaïl
Habiboulaye Amadou Boubacar
Year: 2023
A Review of Computer-Assisted Techniques Performances in Malaria Diagnosis
IOTCARE
Springer
DOI: 10.1007/978-3-031-33545-7_1
Abstract
Malaria belongs to the class of the deadliest infectious diseases in the world. The generally available tools to diagnose this disease, the microscopy and rapid diagnostic test (RDT), have many limitations. Alternative diagnostic techniques with superior results are inaccessible to developing countries with more prevalent cases. Early detection of the infection is critical. Computer-assisted methods are needed. This study surveys the performance of the computer-assisted techniques used in malaria diagnosis and the preprocessing techniques to render the data usable. The survey illustrates, compares and discusses computer-assisted methods results, considering different performance metrics. It highlights how artificial intelligence can strengthen the fight against disease.
