Radiology patients are confident artificial intelligence will improve healthcare workflow and efficiency, but they’re skeptical of the tech itself and remain unsure of how AI will factor into the patient experience, according to a study published online March 14 in the Journal of the American College of Radiology.
A multitude of recent studies and success stories suggest artificial intelligence is on its way to topping doctors in accurately diagnosing diseases from asthma to breast cancer—seemingly a step in the right direction. But does the hype surrounding AI’s victories eclipse its shortcomings?
Artificial intelligence shows great promise in recognizing patterns, liberating physicians from keyboards and predicting outcomes, but where does it fall short? Medical guru Eric Topol does a deep dive into those topics and many more in his new book, Deep Medicine.
NVIDIA this week announced plans to buy chipmaker and its collaboration partner Mellanox Technologies for $6.9 billion. The move by the graphics chip giant seeks to help it push into the growing market for data center components by adding to chips that help speed the flow of information across servers.
Norman E. Sharpless, MD, director of the National Cancer Institute (NCI) since October 2017, has been announced as the new acting commissioner of the FDA. Sharpless replaces Scott Gottlieb, MD, who unexpectedly resigned from the position on March 5.
A deep neural network crafted by research specialists at Dartmouth’s Norris Cotton Cancer Center identified different types of lung adenocarcinoma as well as practicing pathologists in a recent study, according to work published March 4 in Scientific Reports.
A 14-week health technology “sprint” sponsored by the U.S. Census Bureau and coordinated by HHS has produced an AI tool that developers claim could revolutionize the way researchers match cancer patients with clinical trials.