Artificial Intelligence

An artificial intelligence (AI) software designed by Google DeepMind and U.K. physicians identified diseases on optical coherence tomography scans and made the correct referral choice in 94 percent of cases, according to a recent Nature Medicine report.
Researchers at Massachusetts Institute of Technology (MIT) have created a machine-learning technique that reduces the toxic chemotherapy and radiotherapy doses for patients with the most aggressive form of brain cancer.
An artificial intelligence (AI) platform created at Mount Sinai Health System in New York can accurately read a CT scan and diagnose a neurological illness, such as stroke in 1.2 seconds—outperforming its human counterpart.
The center will serve as a common space for University of California, Irvine (UCI) faculty, physicians and researchers to collaborate on translating artificial intelligence (AI)-based concepts into clinical tools to improve all aspects of healthcare.
A new artificial intelligence (AI) algorithm developed by researchers from the Lawson Health Research Institute in Ontario, Canada and The Mind Research Network in Albuquerque, New Mexico, could help predict whether a patient will successfully respond to medication for a mood disorder.  
“Despite some of the earlier market hype, it is becoming increasingly clear that AI will transform the diagnostic imaging industry, both in terms of enhanced productivity, increased diagnostic accuracy, more personalized treatment planning, and ultimately, improved clinical outcomes."
Canon Medical Research Europe, based in Edinburgh, Scotland, was awarded $180,000 to develop an artificial intelligence (AI)-based medical imaging technology prototype that can recognize, assess and measure asbestos-related cancer tumors, according to a report published Aug. 6 by Scottish Business Insider.
The Radiological Society of North America (RSNA) has launched new webinars and workshops aimed at educating radiologists, researchers and industry scientists about artificial intelligence (AI) and machine learning in medical imaging, according to an Aug. 2 RSNA press release.  
Developing a personalized radiation therapy plan can take days—time that many cancer patients are unwilling to wait. But researchers have developed a new automated artificial intelligence (AI) software that can do the job in 20 minutes.
New research from the Massachusetts Institute of Technology (MIT) suggests a physician's intuition—or, in other words, gut feeling—about a patient’s condition significantly influences the amount of diagnostic imaging, which is well above the capabilities of artificial intelligence (AI).
An automated deep learning-based system can accurately evaluate knee joint cartilage to detect wear and injury, according to a recent Radiology study.
According to the world of Twitter, the implementation of artificial intelligence (AI) in radiology renders an overwhelmingly positive response and is joined with arguments against AI potentially replacing radiologists, wrote authors Julia Goldberg, and Andrew Rosenkrantz, MD, in a piece published July 23 in Current Problems in Diagnostic Radiology.
The U.S. Department of Veterans Affairs (VA) and IBM Watson Health have extended their partnership leveraging artificial intelligence (AI) to help analyze cancer data in veterans with the disease.
Artificial intelligence (AI) has the potential to revolutionize patient-care and serve as a valuable tool for radiologists. But with all its promise, a recent editorialist asked: Has anyone thought about how it will all be paid for? And by whom?
Plenty of warnings have been offered about radiology's impending doom thanks to artificial intelligence (AI). Phil Shaffer, a radiologist at Riverside Radiology and Interventional Associates in Columbus, Ohio, offered a response with an opinion piece in The Scientist.
Artificial intelligence (AI) is becoming an essential part of radiology, meaning the industry must consider ethics for computers and AI, according to an opinion piece by Marc Kohli, MD, and Raym Geis, MD, published July 15 in the Journal of the American College of Radiology.  
Artificial Intelligence
Jul 16, 2018 | Imaging Informatics
An AI software developed by researchers from NVIDIA, Aalto University in Finland and MIT may be able to fix low-resolution, grainy or pixelated medical images without previously observing examples of noise-free images.
Imaging Informatics, Artificial Intelligence
A machine learning algorithm trained to analyze MRI images identified schizophrenia patients with 78 percent accuracy, according to a recent study published in Molecular Psychiatry.
Artificial Intelligence
An integrated computer-aided diagnosis (CAD) system developed by researchers from Kyung Hee University and Sungkyunkwan University in South Korea could outperform current conventional deep learning methodologies used by radiologists to detect, segment and classify tumors from digital x-ray mammograms.
Artificial Intelligence, Breast Imaging
IBM Watson Health and medical imaging contrast agent company Guerbet have entered a strategic partnership to develop artificial intelligence (AI) software to support liver cancer diagnostics and care by utilizing CT and MRI technology.
Artificial Intelligence, Oncology Imaging
A deep learning algorithm deployed at MD Anderson Cancer Center in Houston successfully automated and standardized clinical target volumes (CTVs) for radiation therapy in head and neck cancer patients.
Artificial Intelligence, Oncology Imaging