There was nothing virtual about the interest in AI at the virtual annual meeting of the Radiological Society of North America Nov. 29 to Dec. 5.
Despite the lack of actual foot traffic, more than 105 exhibitors presented AI-specific wares in the virtual AI showcase. That was down from 2019’s pre-COVID 150 or so but still easily beat 2018’s head count, around 75.
Meanwhile the 2020 show’s scientific sessions and press conferences broke several noteworthy developments. Here are links to coverage of five (in no special order):
AI spots 18% more stroke patients eligible for treatment compared to radiologists (Health Imaging)
Deep learning predicts woman’s risk for breast cancer (RSNA newsroom)
AI model aids in TB detection via smartphone (RSNA newsroom)
Heart attack and stroke predictable by AI measures of abdominal fat (Health Imaging)
Machine learning model fills gaps in Alzheimer’s diagnosis (RSNA newsroom)
Dave P. has worked in journalism, marketing and public relations for more than 30 years, frequently concentrating on hospitals, healthcare technology and Catholic communications. He has also specialized in fundraising communications, ghostwriting for CEOs of local, national and global charities, nonprofits and foundations.