As machine learning (ML) continues to play a larger role in radiology, it is crucial for future generations of radiologists to receive proper training that helps them participate in its development and implementation, according to a new analysis published in the Journal of the American College of Radiology.
Artificial intelligence (AI) and blockchain are two titanic trends driving the future of medical imaging, according to an in-depth analysis published in the Journal of the American College of Radiology. The study’s authors also assessed other trends that continue to gain momentum.
DeepRay, a new solution from Cambridge Consultants, uses artificial intelligence (AI) to improve distorted or damaged images. The company has said this technology could provide significant value to healthcare providers by improving medical imaging data.
New software that uses artificial intelligence (AI) to diagnose chronic thromboembolic pulmonary hypertension (CTEPH) will receive an expedited review from the FDA as part of the agency’s breakthrough devices program. The program, first established in 2017 as part of the 21st Century Cures Act, is designed to speed up the development of devices and ensure timely patient access.
Radiologist Paul Chang, MD, medical director of enterprise imaging at the University of Chicago, began his presentation Tuesday, Nov. 27, at RSNA 2018 by saying radiologists were in need of a reality check when it comes to artificial intelligence (AI).
Medical imaging equipment is highly susceptible to cyberattacks, putting hospitals and imaging centers at a serious risk of losing functionality of those systems and even having data stolen by an outside entity. This concerning issue is the focus of two studies being presented at RSNA 2018 in Chicago.
As time goes on, artificial intelligence (AI) is becoming more widely accepted as a necessary component of clinical workflow in medical imaging. According to Tarik K. Alkasab, MD, PhD, a radiologist at Massachusetts General Hospital in Boston, AI has the potential to make radiology reporting much more consistent and ultimately help radiologists make smarter decisions.
The New York University (NYU) School of Medicine's department of radiology is releasing a knee MRI dataset of more than 1.5 million anonymous images as part of its ongoing collaboration with Facebook to make MRI scans 10 times faster with artificial intelligence (AI).
During her speech Sunday, Nov. 25, at the opening session of RSNA 2018 in Chicago, RSNA President Vijay Rao, MD, noted that today's radiologists will be empowered by new technologies, not replaced by them.