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Explaining ensemble models for lung ultrasound classification

Academic Article
Publication Date:
2023
abstract:
Correct classification is the main aspect in evaluating the quality of an artificial intelligence system, but what happens when you reach top accuracy and no method explains how it works? In our study, we aim at addressing the black-box problem using an ad-hoc built classifier for lung ultrasound images.
Iris type:
01.01 Articolo in rivista
Keywords:
Explainable artificial intelligence; Image classification; Ensemble models; Lung ultrasound
List of contributors:
Bruno, Antonio; Ignesti, Giacomo; Martinelli, Massimo
Authors of the University:
MARTINELLI MASSIMO
Handle:
https://iris.cnr.it/handle/20.500.14243/462364
Full Text:
https://iris.cnr.it//retrieve/handle/20.500.14243/462364/177006/prod_482760-doc_199263.pdf
Published in:
ERCIM NEWS
Journal
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URL

https://ercim-news.ercim.eu/en134/special/explaining-ensemble-models-for-lung-ultrasound-classification
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