Artificial Intelligence in Neuroradiology: A Review of Current Topics and Competition Challenges.

There is an expanding body of literature that describes the application of deep learning and other machine learning and artificial intelligence methods with potential relevance to neuroradiology practice. In this article, we performed a literature review to identify recent developments on the topics of artificial intelligence in neuroradiology, with particular emphasis on large datasets and large-scale algorithm assessments, such as those used in imaging AI competition challenges. Numerous applications relevant to ischemic stroke, intracranial hemorrhage, brain tumors, demyelinating disease, and neurodegenerative/neurocognitive disorders were discussed.

The added value of a second read by pediatric radiologists for outside skeletal surveys.

Background: Fractures are the second most common finding in non-accidental trauma after cutaneous signs. Interpreting skeletal surveys could be challenging as some fractures are subtle and due to anatomical variations that can mimic injuries.

Objective: To determine the effect of a second read by a pediatric radiologist of skeletal surveys for suspected non-accidental trauma initially read at referring hospitals by general radiologists.