Here's what to expect this week on Diagnostic Imaging.
In this week’s preview, here are some highlights of what you can expect to see coming soon on Diagnostic Imaging:
RSNA 2020 is in the books, but that does not mean coverage on Diagnostic Imaging stops. The conference still has a great deal to offer. Later this week, look for the third, and final, installment of videos with David Larson, M.D., professor of radiology at Stanford University, focusing on the ethical questions and challenges surrounding the use of artificial intelligence with patient data and medical imaging.
For the previous two videos with Larson, as well as other RSNA 2020 coverage, click here.
For more coverage based on industry expert insights and research, subscribe to the Diagnostic Imaging e-Newsletter here.
As the country rounds into the holidays and toward the New Year, cases of COVID-19 are, once again, surging. That makes it all the more critical for providers to be able to identify patients who are infected with the virus and, potentially, learn who will fare better or worse. New research is out this week focusing on this issue – Diagnostic Imaging will report on the role imaging plays later this week.
For additional reporting on the use of imaging to diagnose and assess COVID-19 patients, click here.
Since March, 2020 has been a rough, demanding year, putting radiology in the middle of the worst healthcare crisis seen in a century. But, dealing with the pandemic is not the only health-related event throughout the past 12 months. While radiologists and other healthcare providers were focused on the emergent needs, advancements were still marching on in other areas of medical imaging. This week, Diagnostic Imaging will share some the biggest developments of the year in mammography.
For additional mammography coverage, click here.
European Society of Breast Imaging Issues Updated Breast Cancer Screening Recommendations
April 24th 2024One of the recommendations from the European Society of Breast Imaging (EUSOBI) is annual breast MRI exams starting at 25 years of age for women deemed to be at high risk for breast cancer.
Could a Deep Learning Model for Mammography Improve Prediction of DCIS and Invasive Breast Cancer?
April 15th 2024Artificial intelligence (AI) assessment of mammography images may significantly enhance the prediction of invasive breast cancer and ductal carcinoma in situ (DCIS) in women with breast cancer, according to new research presented at the Society for Breast Imaging (SBI) conference.