Background and purpose In comparison to conventional medical imaging diagnostic
modalities, the aim of this overview article is to analyze the accuracy of the application of …

To reduce the number of missed or misdiagnosed lung nodules on CT scans by radiologists,
many Artificial Intelligence (AI) algorithms have been developed. Some algorithms are …

Background There has been growing interest in using artificial intelligence/deep learning
(DL) to help diagnose prevalent diseases earlier. In this study we sought to survey the …

Early detection and identification of malignant lung nodules improve the survival of lung
cancer patients. The visual attributes such as subtlety, spiculation, and calcification of lung …

Introduction There are limited data on chest computed tomography (CT) findings in the
assessment of lung nodules among adult Aboriginal Australians. In this retrospective study …

Purpose To develop a comprehensive multi-classification model that combines radiomics
and clinic-radiological features to accurately predict the invasiveness and differentiation of …

Background: Alzheimer's disease (AD), a major dementia cause, lacks effective treatment.
MRI-based hippocampal volume measurement using artificial intelligence offers new …

Background This study aims to assess the performance of an established an AI algorithm
trained on conventional polychromatic computed tomography (CT) images (CPIs) to detect …

Background The prevalence of lung cancer in the Middle East and Africa (MEA) region has
steadily increased in recent years and is generally associated with a poor prognosis due to …

Background The ability of lung cancer screening to manage pulmonary nodules was limited
because of the high false‐positive rate in the current mainstream screening method, low …