What question did this study set out to answer?

This research aims to create a deep learning system for detecting the COVID-19 virus using chest CT scans.

February 22, 2026International Journal of Medical Engineering and Informatics0 citations

Diagnosis of the COVID-19 with deep learning

MDMouloud Demouche ABAbderrahmane Baadache DADjamil Aı̈ssani

Key Points

This research aims to create a deep learning system for detecting the COVID-19 virus using chest CT scans.
Developed three convolutional neural network (CNN) models
Applied models to a publicly available COVID-19 chest CT scan dataset
Evaluated performance using F1-score
The InceptionResNetV2 model achieved a high F1-score of 98.5%
The models effectively detect COVID-19 in chest CT scans

Abstract

Since the beginning of 2020, the COVID-19 virus has spread widely throughout the world. RT-PCR is used to diagnose the disease, but radiologists studied advances in chest CT scans to produce high-quality images. The purpose of this research is to develop a deep learning system for detecting the COVID-19 virus using chest computed tomography. We proposed three convolutional neural network (CNN) approaches to developed three models, and applied them to a publicly available COVID-19 screening chest CT scan dataset of 2,482 images. Our models have shown that they work by getting a high F1-score of 98.5% for the InceptionResNetV2 model.

AIに質問

Bookmark

View Full Paper