Aided by artificial intelligence, analysis of retinal images and related data identified condition-specific features that distinguished patients with mild cognitive impairment from those with normal cognition, a prospective study showed.

Artificial intelligence was able to reduce radiologists’ mammography screen-reading workload by 44%, according the results of a randomised control trial.

There were several key hot topics to discuss at the American Society of Echocardiography (ASE) 2023 annual meeting. Among these were a push to adopt commercially available AI solutions, a focus on how to diagnose cardiac amyloid and hypertrophic cardiomyopathy now that there are drug treatments, and the nationwide shortage of sonographers.

One of the biggest issues in echocardiography is the inconsistency between how sonographers scan patients and make measurements. However, AI might be able to help overcome this variable and make cardiac ultrasound quantification more consistent. This is especially true for novice sonographers using point-of-care ultrasound (POCUS), where AI is being commercialised.

Surveying the landscape of interpretive AI in radiology, two researchers note a yawning gap between great expectations set in the recent past and actual clinical implementations as of spring 2023.

Following ChatGPT’s strong performance on a mock radiology board exam, experts are calling for radiology training programs to rethink how they are educating residents.

Philips has developed an AI-powered CT system that increases throughput and improves image quality, all while decreasing patient exposure to ionizing radiation.

Not to be outdone by OpenAI’s ChatGPT, Google recently introduced the latest version of its own large language model (LLM), which could be particularly beneficial within the realm of medical imaging, according to CEO Sundar Pichai.

Although artificial intelligence assistance has proven to be of great benefit to radiologists interpreting mammograms, new data bring pause to experts’ optimism relative to AI, due to the bias it can spark. A new paper published in Radiology highlights how automation bias can impair the performance of radiologists across a range of experience levels, even the...

An artificial intelligence-based model has the potential to improve follow-up adherence for radiologist-recommended additional imaging (RAI). The AI model could have great utility in ensuring patients undergo radiologist-recommended follow-up imaging, experts involved in the study suggested.