Application of machine and deep learning algorithms in optical microscopic detection of Plasmodium: A malaria diagnostic tool for the future
Authors:
- Charles IkerionwuCICharles Ikerionwu
- Chikodili UgwuishiwuChikodili Ugwuishiwu
- Izunna OkpalaIOIzunna Okpala
- Idara JamesIJIdara James
- Matthew OkoronkwoMOMatthew Okoronkwo
- Charles NnadiCNCharles Nnadi
- Ugochukwu OrjiUOUgochukwu Orji
- Deborah EbemDEDeborah Ebem
- Anthony IkeAIAnthony Ike
- 13 November 2022
- journal article
- research article
- Published by Elsevier in Photodiagnosis and Photodynamic Therapy
- Vol. 40
Abstract
No abstract availableKeywords
This publication has 140 references indexed in Scilit:
- Developing standards for malaria microscopy: external competency assessment for malaria microscopists in the Asia-PacificMalaria Journal, 2012
- Estimating malaria parasite density: assumed white blood cell count of 10,000/μl of blood is appropriate measure in Central GhanaMalaria Journal, 2012
- Taste for Blood: Hemoglobin as a Nutrient Source for PathogensPLOS Pathogens, 2012
- Performance of HRP-2 based rapid diagnostic test for malaria and its variation with age in an area of intense malaria transmission in southern tanzaniaMalaria Journal, 2010
- Use of RDTs to improve malaria diagnosis and fever case management at primary health care facilities in UgandaMalaria Journal, 2010
- Revisiting the circulation time of Plasmodium falciparum gametocytes: molecular detection methods to estimate the duration of gametocyte carriage and the effect of gametocytocidal drugsMalaria Journal, 2010
- Malaria Diagnosis: A Brief ReviewThe Korean Journal of Parasitology, 2009
- Malaria Parasite Pre-Erythrocytic Stage Infection: Gliding and HidingCell Host & Microbe, 2008
- Computer-aided diagnosis in medical imaging: Historical review, current status and future potentialComputerized Medical Imaging and Graphics, 2007
- Genome sequence of the human malaria parasite Plasmodium falciparumNature, 2002