The GA-ANN model had the best classification performances when detecting subjects with cement dust exposure, compared with several machine learning models.
This study develops an artificial neural network (ANN) model for identifying cement dust-exposed (CDE) subjects using quantitative computed tomography-based ...
Oct 22, 2024 · This study develops an artificial neural network (ANN) model for identifying cement dust-exposed (CDE) subjects using quantitative computed ...
Quantitative computed tomography imaging-based classification of cement dust-exposed subjects with an artificial neural network technique ... Authors: Taewoo Kim ...
Oct 7, 2024 · Quantitative computed tomography imaging-based classification of cement dust-exposed subjects with an artificial neural network technique.
Background: Dust exposure has been reported as a risk factor of pulmonary disease, leading to alterations of segmental airways and parenchymal lungs.
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Quantitative computed tomography imaging-based classification of cement dust-exposed subjects with an artificial neural network technique · Author Picture Taewoo ...
This study aims to investigate alterations of quantitative computed tomography (QCT)-based airway structural and functional metrics due to cement-dust exposure.
Missing: classification neural network
Quantitative computed tomography imaging-based clustering differentiates asthmatic subgroups with distinctive clinical biomarkers, Journal of Allergy and ...
Quantitative computed tomography imaging-based classification of cement dust-exposed subjects with an artificial neural network technique. Taewoo Kim, Woo ...