Radiology reports are typically written in language well above the average American adult’s eighth grade reading level, making them a source of confusion for patients.
The lead-up to radiation therapy can be anxiety-inducing and painful, but experts are optimistic a new relaxation method that is equal parts ancient and futuristic could help to ease patients’ worries.
The tool uses a machine learning technique to identify changes on brain MRIs that would otherwise be overlooked by radiologists due to the subtlety of alterations.
Trauma patients who present with poor blood flow and suspected abdominal hemorrhage are well served by emergency physicians using AI-augmented FAST imaging.
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.
The majority of radiology trainees have expressed interest in furthering their knowledge of artificial intelligence applications in the field, yet few are offered the opportunity to do so during the course of their education, according to new survey data.
A multi-modal AI approach can combine information from both ABUS and DM, which could be especially beneficial in resource poor regions where experienced radiologists might not be readily available.
The Edinburgh-based business made the announcement on Jan. 18, noting that the acquisition will build on the company’s goals to “improve the lives of patients and populations by unlocking the adoption and benefits of medical imaging AI.”
The deep learning model was trained to predict risk of lung cancer in the one to six years following completion of an LDCT scan, and it does not require clinical information relative to risk factors to do so.
