Top People to Watch in Radiology
Diagnostic Imaging’s inaugural “Top People to Watch in Radiology” contest profiles today's top radiologist, technologist, researcher, and group.
[[{"type":"media","view_mode":"media_crop","fid":"28210","attributes":{"alt":"","class":"media-image","id":"media_crop_2984776295384","media_crop_h":"0","media_crop_image_style":"-1","media_crop_instance":"2833","media_crop_rotate":"0","media_crop_scale_h":"0","media_crop_scale_w":"0","media_crop_w":"0","media_crop_x":"0","media_crop_y":"0","style":"height: 250px; width: 250px; border-width: 0px; border-style: solid; margin: 1px;","title":" ","typeof":"foaf:Image"}}]]Diagnostic Imaging’s inaugural “Top People to Watch in Radiology” contest profiles the radiologist, technologist, researcher, and group proven to be superstars in medical imaging.
Nominate the radiology professional or group that stand out from the crowd for doing something different and great and you’ll be entered into a raffle to win a $100 gift card.
We’ll post the nominees for the “Top People to Watch in Radiology” and let our readers vote on who gets the honors. Nominees must be US-based. We’ll be accepting nominations through October 24, 2014.
Read full contest rules here.
The Reading Room: Artificial Intelligence: What RSNA 2020 Offered, and What 2021 Could Bring
December 5th 2020Nina Kottler, M.D., chief medical officer of AI at Radiology Partners, discusses, during RSNA 2020, what new developments the annual meeting provided about these technologies, sessions to access, and what to expect in the coming year.
Can AI Improve Triage Efficiency in Radiology Workflows for Follow-Up X-Rays?
October 24th 2023An emerging deep learning algorithm can reportedly triage 40 percent of no-change X-rays while providing 88 to 90 percent accuracy for detecting changes with X-rays obtained in the emergency department and intensive care unit at a tertiary referral hospital, according to recently published research.
