Artificial Intelligence

Machine learning might be the next step in predicting patient wait times and appointment delays—factors crucial to healthcare’s quadruple aim and its emphasis on quality of care—in radiology practices, researchers have reported in the Journal of the American College of Radiology.
A robotic needle-placement system outfitted with correction software to improve its accuracy in mechanizing computed tomography (CT)-guided needle placement, according to a study published ahead of print in the Journal of Vascular and Interventional Radiology.
Densitas, a medical device company based out of Halifax, Nova Scotia, Canada, announced that DENSITAS|density, its software that uses machine learning to produce breast density reports, has gained FDA clearance.
Elad Walach, founder and CEO of the medical imaging company Aidoc, is one of many in the industry who believes radiology will be transformed by artificial intelligence (AI) sooner rather than later. He went into detail on the topic in a new column published in Forbes.
Radiology supercomputer “Project Clara” could improve imaging quality while speeding up the detection of fatal diseases like cancer and heart failure, Forbes has reported.
Despite radiology’s love-hate relationship with artificial intelligence (AI), advancements could afford the field an opportunity to “hit refresh” and reinvent itself, Emory University professor and radiologist Srini Tridandapani, PhD, MD, MSCR, wrote in Academic Radiology this month.
As online learning options for radiology continue to grow, some students are turning to Second Life—a virtual community developed by its own users and reigned by avatars—to complete their medical education, researchers in Malaga, Spain, have found.
Brainomix, a U.K.-based medical imaging company focused on artificial intelligence (AI), announced Tuesday, April 3, that it has secured $9.8 million (£7 million) to help market its software for treating stroke victims throughout the world.
A team of Ohio State University radiologists have developed artificial intelligence (AI) that can not only analyze hundreds of CT scans within minutes, but can detect the presence and urgency of hemorrhages, masses, hydrocephalus and stroke, according to the university’s paper, the Lantern.
Seattle radiologist Maria Chong, MD, a body imaging specialist for Radia, said in a new interview that artificial intelligence (AI) and machine learning will “revolutionize radiology” in the next decade.
As the influence of artificial intelligence (AI) and machine learning (ML) continues to spread throughout medical imaging, radiology training programs may need to update their curricula and prepare for both the short- and the long-term effects of these new technologies, according to a new commentary published in Academic Radiology.
Nvidia, a Santa Clara, California-based technology company, announced the winners of its Inception contest for the best artificial intelligence (AI) startups at this year’s GPU Technology Conference (GTC) in San Jose. One of those winners, Subtle Medical, is focused on improving medical imaging by improving exam times and costs.
Ever since artificial intelligence (AI) became one of the biggest topics in radiology, there has been a debate about whether AI would eventually replace radiologists.
Artificial intelligence might be a hot tech topic, but it could also pose ethical risks—namely racial ones—to healthcare, Clinical Innovation + Technology reported this month.
A novel machine learning model could accurately predict which men might benefit most from additional imaging before a prostate biopsy, saving patients both money and discomfort, a new study states.
Machine learning might be the next step in predicting patient wait times and appointment delays—factors crucial to healthcare’s quadruple aim and its emphasis on quality of care—in radiology practices, researchers have reported in the Journal of the American College of Radiology.
A robotic needle-placement system outfitted with correction software to improve its accuracy in mechanizing computed tomography (CT)-guided needle placement, according to a study published ahead of print in the Journal of Vascular and Interventional Radiology.
Densitas, a medical device company based out of Halifax, Nova Scotia, Canada, announced that DENSITAS|density, its software that uses machine learning to produce breast density reports, has gained FDA clearance.
Elad Walach, founder and CEO of the medical imaging company Aidoc, is one of many in the industry who believes radiology will be transformed by artificial intelligence (AI) sooner rather than later. He went into detail on the topic in a new column published in Forbes.
Radiology supercomputer “Project Clara” could improve imaging quality while speeding up the detection of fatal diseases like cancer and heart failure, Forbes has reported.
Despite radiology’s love-hate relationship with artificial intelligence (AI), advancements could afford the field an opportunity to “hit refresh” and reinvent itself, Emory University professor and radiologist Srini Tridandapani, PhD, MD, MSCR, wrote in Academic Radiology this month.