Artificial intelligence (AI) and informatics promise to improve the quality and efficiency of diagnostic radiology but will require substantially more standardization and operational coordination to realize and measure those improvements….

We present an overview of current clinical musculoskeletal imaging applications for artificial intelligence, as well as potential future applications and techniques. Key points • Deep learning for MSK imaging can…

The potential of artificial intelligence (AI) in radiology goes far beyond image analysis. AI can be used to optimize all steps of the radiology workflow by supporting a variety of…

Organ segmentation, chest radiograph classification, and lung and liver nodule detections are some of the popular artificial intelligence (AI) tasks in chest and abdominal radiology due to the wide availability…

No one knows what the paradigm shift of artificial intelligence will bring to medical imaging. In this article, we attempt to predict how artificial intelligence will impact radiology based on…

Although recent scientific studies suggest that artificial intelligence (AI) could provide value in many radiology applications, much of the hard engineering work required to consistently realize this value in practice…

The radiology reporting process is beginning to incorporate structured, semantically labeled data. Tools based on artificial intelligence technologies using a structured reporting context can assist with internal report consistency and…

Radiologists have been at the forefront of the digitization process in medicine. Artificial intelligence (AI) is a promising area of innovation, particularly in medical imaging. The number of applications of…

Natural language processing (NLP) is a subfield of computer science and linguistics that can be applied to extract meaningful information from radiology reports. Symbolic NLP is rule based and well…