Using a fully-automated artificial intelligence (AI) deep learning model, researchers were able to identify early signs of type 2 diabetes on abdominal CT scans, according to a new study published in the journal Radiology.
Type 2 diabetes affects approximately 13% of all U.S. adults and an additional 34.5% of adults meet the criteria for prediabetes. Due to the slow onset of symptoms, it is important to diagnose the disease in its early stages. Some cases of pre-diabetes can last up to 8 years and an earlier diagnosis will allow patients to make lifestyle changes to alter the progression of the disease… Continue reading.
Researchers at the National Institutes of Health and the University of Wisconsin have demonstrated that using artificial intelligence to analyze CT scans can produce more accurate risk assessment for major cardiovascular events than current, standard methods such as the Framingham risk score (FRS) and body-mass index (BMI).
More than 80 million body CT scans are performed every year in the U.S. alone, but valuable prognostic information on body composition is typically overlooked. In this study, for example, abdominal scans done for routine colorectal cancer screening revealed important information about heart-related risks – when AI was used to analyze the images… Continue reading.
WASHINGTON, D.C.—The American Institute for Medical and Biological Engineering (AIMBE) has announced the induction of Ronald Summers, MD, Ph.D., Senior Investigator, Radiology and Imaging Sciences, National Institutes of Health Clinical Center, to its College of Fellows.
Election to the AIMBE College of Fellows is among the highest professional distinctions accorded to a medical and biological engineer. The College of Fellows is comprised of the top two percent of medical and biological engineers. College membership honors those who have made outstanding contributions to “engineering and medicine research, practice, or education” and to “the pioneering of new and developing fields of technology, making major advancements in traditional fields of medical and biological engineering, or developing/implementing innovative approaches to bioengineering education.”
Dr. Summers was nominated, reviewed, and elected by peers and members of the College of Fellows for “outstanding contributions to computer-assisted interpretation of radiology images.”