The diagnosis and treatment of patients with cancer requires access to imaging to ensure
accurate management decisions and optimal outcomes. Our global assessment of imaging …

Artificial intelligence (AI) will change the face of nuclear medicine and molecular imaging as
it will in everyday life. In this review, we focus on the potential applications of AI in the field …

Background Intratumor heterogeneity in lung cancer may influence outcomes. CT radiomics
seeks to assess tumor features to provide detailed imaging features. However, CT radiomic …

Objectives Performance of recently developed deep learning models for image classification
surpasses that of radiologists. However, there are questions about model performance …

Recent works have shown that deep neural networks can achieve super-human
performance in a wide range of image classification tasks in the medical imaging domain …

Previous studies on automating building design with deep learning primarily focused on
planning room layouts, limiting the design of architectural elements such as doors and …

At the beginning of the COVID-19 pandemic, there was significant hype about the potential
impact of artificial intelligence (AI) tools in combatting COVID-19 on diagnosis, prognosis, or …

COVID-19 has caused a pandemic crisis that threatens the world in many areas, especially
in public health. For the diagnosis of COVID-19, computed tomography has a prognostic role …

Alzheimer's disease (AD) is a non-treatable and non-reversible disease that affects about
6% of people who are 65 and older. Brain magnetic resonance imaging (MRI) is a pseudo …

With advanced neural network techniques, language models can generate content that
looks genuinely created by humans. Such advanced progress benefits society in numerous …