Radiologists use diagnostic imaging to non-invasively look inside the body to help determine the causes of an injury or an illness, and confirm a diagnosis. Providers use many imaging modalities to do so, including CT, MRI, X-ray, Ultrasound, PET and more.
"Lp(a) represents the most important potential potential paradigm shift in cardiovascular disease prevention that we'll experience over the next five to 10 years," Seth Baum, MD, explained in a new interview.
Generative artificial intelligence models have shown great potential for improving multiple aspects of the radiology field, but a new analysis cautions that they still require significant oversight.
If left undiagnosed and untreated for a prolonged period, fatty liver disease can progress to more serious conditions, such as cirrhosis and liver cancer.
The FDA clearly sees significant potential in a new multi-protein blood test from Prevencio. The company's goal is to gain full approval and get the test in the hands of emergency departments all over the United States.
Radiology education researchers have created an image-intensive online course for third- and fourth-year medical students wishing to learn radiology remotely.
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.
Not only could the materials reduce patient exposure to ionizing radiation, they also could reduce costs associated with traditional X-ray equipment, according to newly published research in Nature Communications.
Experts from Mayo Clinic recently detailed their experience with the new offering, sharing that out of their 10 top ranked candidates, six had signaled the program.
Features pertaining to location, density and superimposed structures were recently found to be associated with poorer outcomes for patients who initially had their lung cancer overlooked on radiographs.
The Australia-based company made the announcement on April 12 in a release that described the timing of these AI-assisted solutions as “increasingly important” amid growing workloads and staffing shortages.
Radiologists used an AI tool-building platform to create their model(s), which allows clinicians the opportunity to develop AI models without any prior training in data sciences or computer programming.