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.
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 inAcademic 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.