Artificial Intelligence

The Royal Australian and New Zealand College of Radiologists (RANZCR) has established a working group to research the impact and influence of artificial intelligence (AI) on healthcare, focusing specifically on radiology. 

Recent research has suggested that artificial intelligence (AI) may be keeping students from considering radiology as a career. The author of a letter to the editor published in Academic Radiology, however, noted that interest in radiology appears to be growing. 

Researchers used a convolutional neural network (CNN) to classify acute and non-acute findings in pediatric elbow x-rays, according to new research published in Radiology: Artificial Intelligence. The team’s recurrent neural network was able to interpret an entire series of images together, mimicking the decision-making process of a human radiologist.

Oxipit, a medical imaging solutions manufacturer based out of Vilnius, Lithuania, announced that its ChestEye imaging suite has received CE certification.

Object detection convolutional neural networks (CNNs) can detect and localize fractures in wrist x-rays, according to a new study published in Radiology: Artificial Intelligence.

RSNA has published the debut issue of its new online journal, Radiology: Artificial Intelligence.

Though artificial intelligence continues to make great strides within radiology, some radiologists are still unprepared to educate medical students regarding its usage, according to a new commentary published in Academic Radiology.

The Alliance for Artificial Intelligence in Healthcare (AAIH) announced that it has officially launched after holding the inaugural meeting of its board of directors Jan. 9 in San Francisco.

At the World Economic Forum in Davos, Switzerland, Alphabet CFO Ruth Porat detailed the significant impact artificial intelligence (AI) technologies are having on breast cancer care

Researchers have trained an artificial intelligence (AI) system to prioritize chest x-rays containing critical findings, according to a new study published in Radiology.

Healthcare, including imaging, is one of 13 industries that will soon be “revolutionized" by artificial intelligence (AI) and machine learning (ML) technologies, according to a new report published in Forbes.

Artificial intelligence (AI) can be trained to predict a patient’s likelihood of axillary lymph node metastasis using a breast MRI dataset, according to a study published in the Journal of Digital Imaging.