Abstract
The computer vision diagnostic approach currently generates several malaria diagnostic tools. It enhances the accessible and straightforward diagnostics that necessary for clinics and health centers in malaria-endemic areas. A new computer malaria diagnostics tool called the malaria scanner was used to investigate living malaria parasites with easy sample preparation, fast and user-friendly. The cultured Plasmodium parasites were used to confirm the sensitivity of this technique then compared to fluorescence-activated cell sorting (FACS) analysis and light microscopic examination. The measured percentage of parasitemia by the malaria scanner revealed higher precision than microscopy and was similar to FACS. The coefficients of variation of this technique were 1.2-6.7% for Plasmodium knowlesi and 0.3-4.8% for P. falci-parum. It allowed determining parasitemia levels of 0.1% or higher, with coefficient of variation smaller than 10%. In terms of the precision range of parasitemia, both high and low ranges showed similar precision results. Pearson’s correlation test was used to evaluate the correlation data coming from all methods. A strong correlation of measured parasitemia (r2 = 0.99, P < 0.05) was observed between each method. The parasitemia analysis using this new diagnostic tool needs technical improvement, particularly in the differentiation of malaria species.
| Original language | English |
|---|---|
| Pages (from-to) | 113-119 |
| Number of pages | 7 |
| Journal | Korean Journal of Parasitology |
| Volume | 59 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 2021 |
Bibliographical note
Publisher Copyright:© 2021, Korean Society for Parasitology and Tropical Medicine.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Computer vision
- Diagnosis
- Malaria
- P. falciparum
- Parasitemia
- Plasmodium knowlesi
ASJC Scopus subject areas
- Parasitology
- Infectious Diseases
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