The application of statistical and artificial intelligence (AI) tools in building energy prediction
(BEP) is considered one of the most effective advances toward improving energy efficiency …

Many researchers working on cancer diagnosis have implemented research design in the
past decade, implementing its proposed techniques. This section is dedicated to …

Advent of advanced imaging technology and better neuro-interventional equipment have
resulted in timely diagnosis and effective treatment for acute ischemic stroke (AIS) due to …

The purpose of this study is to assess feasibility of developing a new case-based computer-
aided diagnosis (CAD) scheme of mammograms based on a tree-based analysis of SSIM …

Applying computer-aided detection (CAD) generated quantitative image markers has
demonstrated significant advantages than using subjectively qualitative assessment in …

Developing radiomic based machine learning models has drawn considerable attention in
recent years. However, identifying a small and optimal feature vector to build a robust …

Ultrasound imaging is a powerful imaging modality for diagnosing breast tumors due to its
non-invasive nature, real-time imaging capabilities, and lack of ionizing radiation …

Risk prediction models are trained and deployed to analyze images, such as computed
tomography scans, for predicting future risk of lung cancer for one or more subjects …

Gastric cancer is one of the most common malignant tumors with high mortality rate
worldwide. In order to optimally treating gastric cacner patients and reduce cancer mortality …

Brain computed tomography (CT) images have been routinely used by neuroradiologists in
diagnosis of aneurysmal subarachnoid hemorrhage (aSAH). The purpose of this study is to …