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Identification of Cryptosporidium parvum Oocysts by an Artificial Neural Network Approach
Microscopic detection of Cryptosporidium parvum oocysts is time-consuming, requires trained analysts, and is frequently subject to significant human errors. Artificial neural networks (ANN) were developed to help identify immunofluorescently labeled C. parvum oocysts. A total of 525 digitized images...
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| Auteurs principaux: | , , |
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| Format: | Artigo |
| Langue: | Inglês |
| Publié: |
American Society for Microbiology
2002
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| Sujets: | |
| Accès en ligne: | https://ncbi.nlm.nih.gov/pmc/articles/PMC123730/ https://ncbi.nlm.nih.gov/pubmed/11872458 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1128/AEM.68.3.1115-1121.2002 |
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