Countless articles have been written over the years about whether artificial intelligence (AI) could replace radiologists, leading to a Jurassic-like extinction of radiologists.

AI has been applied in many fields, including Medicine, especially in diagnostic imaging. So, what issues should we consider when applying artificial intelligence software - AI in diagnostic imaging? A multinational group of authors has issued new guidelines, with 10 issues based on answering 10 questions. The following article will address the first two issues.

Early cancer prediction and treatment response is a key issue in personalized treatment for cancer patients. Artificial intelligence (AI), a field of computer science, aims to develop algorithms or computer programs with advanced analytical or predictive capabilities. The application of artificial intelligence to early cancer detection can improve diagnostic accuracy, improve clinical decision-making, and lead to revolutionizing the future of diagnosis and treatment.

Recently, a study published in the journal Computer in Biology and Medicine showed that artificial intelligence (AI) can identify kidney stones on CT scans, even when the kidney stones are very small.

Artificial intelligence (AI), especially deep learning models, is a promising innovation in colonoscopy. Recent studies have shown that AI is not only accurate in detecting colorectal polyps but can also reduce the miss rate. However, the application of AI in real-time detection has been hindered by the heterogeneity of AI models and study designs as well as the lack of long-term results.

Can we use chest radiographs to identify underlying coronary artery disease? According to a study published in the journal Cardiothoracic Imaging, artificial intelligence (AI) can identify this.