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Comparison of the capacity of several machine learning tools to assist immunofluorescence-based detection of anti-neutrophil cytoplasmic antibodies

2024-01-28

Abstract excerpt

The success of artificial intelligence and machine learning is an incentive to develop new algorithms to increase the rapidity and reliability of medical diagnosis. Here we compared different strategies aimed at processing microscope images used to detect anti-neutrophil cytoplasmic antibodies, an important vasculitis marker: (i) basic classifier methods (logistic regression, k-nearest neighbors and decision tree)...

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Literature Corpus work
3b818e5d-8407-5ae8-bb13-41863a4a7451
DOI
10.1101/2024.01.26.24301725
Open publication

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Comparison of the capacity of several machine learning tools to assist immunofluorescence-based detection of anti-neutrophil cytoplasmic antibodiesDOI 10.1101/2024.01.26.24301725
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