Automated ANA Pattern Classification using Deep Learning Ensemble Models

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Auteur principal: Abri, Rayan
Format: Recurso digital
Publié: Zenodo 2026
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author Abri, Rayan
author_facet Abri, Rayan
contents Automated classification of Antinuclear Antibody (ANA) patterns from immunofluorescence microscopy images using deep learning ensemble models. This work presents a multi-label classification approach using ResNet50 and EfficientNet-B0 trained on mixed single-label and multi-pattern datasets, achieving 82.25% exact match accuracy on validation data from hospital dataset with 32 ANA pattern classes (AC-0 to AC-31).
format Recurso digital
id zenodo_https___doi_org_10_5281_zenodo_19359168
institution Zenodo
language
publishDate 2026
publisher Zenodo
record_format zenodo
spellingShingle Automated ANA Pattern Classification using Deep Learning Ensemble Models
Abri, Rayan
deep learning
medical imaging
antinuclear antibodies
immunofluorescence
multi-label classification
computer vision
pattern recognition
ensemble learning
Automated classification of Antinuclear Antibody (ANA) patterns from immunofluorescence microscopy images using deep learning ensemble models. This work presents a multi-label classification approach using ResNet50 and EfficientNet-B0 trained on mixed single-label and multi-pattern datasets, achieving 82.25% exact match accuracy on validation data from hospital dataset with 32 ANA pattern classes (AC-0 to AC-31).
title Automated ANA Pattern Classification using Deep Learning Ensemble Models
topic deep learning
medical imaging
antinuclear antibodies
immunofluorescence
multi-label classification
computer vision
pattern recognition
ensemble learning
url https://doi.org/10.5281/zenodo.19359168