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Technology Management

 

As the influence of social media platforms such as Twitter and Facebook grows, healthcare specialists have started adopting specific hashtags on those platforms to reach the largest number of users possible. In interventional radiology, for instance, the preferred hashtag is #IRad. Researchers tracked the evolution of that hashtag on Twitter, publishing their results in the Journal of Vascular and Interventional Radiology.

During a 2016 simulation exercise, researchers evaluated the ability of 32 different deep learning algorithms to detect lymph node metastases in patients with breast cancer. Each algorithm’s performance was then compared to that of a panel of 11 pathologists with time constraint (WTC). Overall, the team found that seven of the algorithms outperformed the panel of pathologists, publishing an in-depth analysis in JAMA.

At RSNA 2017 in Chicago, artificial intelligence (AI) and deep learning technologies were everywhere. Attendees rushed to learn as much as possible about AI, countless educational sessions touched on the topic and exhibitors made sure to mention it in their booths as much as possible. I wouldn’t quite say AI took over the show like some have suggested, but it did make quite an impression on everyone walking through the doors of McCormick Place.

The buzz around social media in radiology has skyrocketed in recent years, with more and more departments, private practices and specialists starting to use using the various platforms to their advantage. Of course, it’s about more than just using sites such as Facebook, Twitter and Instagram; to get the most out of these resources, one must also learn the differences between them.

Interest in artificial intelligence (AI) and machine learning at RSNA 2017 seems like it’s unprecedented—but the increased attention is quantifiable. More than 100 sessions delve into the topic at this year’s show in Chicago. Two years ago, less than 10 touched on such concepts.

 

Recent Headlines

Carestream Health to display AI, imaging analytics solutions at HIMSS18

Carestream Health announced Wednesday, Feb. 21, that it will be displaying advanced artificial intelligence and imaging analytics software tools March 5-9 at HIMSS18 in Las Vegas.

FDA clears 3D MRI application from Siemens

Siemens announced Monday, Feb. 19, that the FDA has cleared the company’s GOKnee3D MRI application.

Canon Medical Systems receives FDA clearance for Vantage Galan 3T XGO Edition

Canon Medical Systems USA announced Monday that the company has received FDA clearance for its new MR system, the Vantage Galan 3T XGO Edition.

Using Twitter to discuss interventional radiology? Make sure you know this hashtag

As the influence of social media platforms such as Twitter and Facebook grows, healthcare specialists have started adopting specific hashtags on those platforms to reach the largest number of users possible. In interventional radiology, for instance, the preferred hashtag is #IRad. Researchers tracked the evolution of that hashtag on Twitter, publishing their results in the Journal of Vascular and Interventional Radiology.

Canon Medical Systems installs new MR system in Ohio research center

Canon Medical Systems USA announced today that, as part of its partnership with Quality Electrodynamics (QED), the company has installed a Vantage Galan 3T MR system at the new QED Research Center in Mayfield Village, Ohio.

Radiologists awarded $50K grant to research prenatal imaging techniques

A team of radiologists and other specialists led by Ali Gholipour, PhD, of Boston Children’s Hospital and Harvard Medical School, has been awarded a $50,000 research grant by the Fetal Health Foundation (FHF).

These deep learning algorithms outperformed a panel of 11 pathologists

During a 2016 simulation exercise, researchers evaluated the ability of 32 different deep learning algorithms to detect lymph node metastases in patients with breast cancer. Each algorithm’s performance was then compared to that of a panel of 11 pathologists with time constraint (WTC). Overall, the team found that seven of the algorithms outperformed the panel of pathologists, publishing an in-depth analysis in JAMA.

RSNA in review: Radiologists ready to make the most of AI

At RSNA 2017 in Chicago, artificial intelligence (AI) and deep learning technologies were everywhere. Attendees rushed to learn as much as possible about AI, countless educational sessions touched on the topic and exhibitors made sure to mention it in their booths as much as possible. I wouldn’t quite say AI took over the show like some have suggested, but it did make quite an impression on everyone walking through the doors of McCormick Place.

RSNA 2017: A radiologist’s guide to the differences between Facebook, Twitter and other social media platforms

The buzz around social media in radiology has skyrocketed in recent years, with more and more departments, private practices and specialists starting to use using the various platforms to their advantage. Of course, it’s about more than just using sites such as Facebook, Twitter and Instagram; to get the most out of these resources, one must also learn the differences between them.

RSNA 2017: AI has potential to match the hype

Interest in artificial intelligence (AI) and machine learning at RSNA 2017 seems like it’s unprecedented—but the increased attention is quantifiable. More than 100 sessions delve into the topic at this year’s show in Chicago. Two years ago, less than 10 touched on such concepts.

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