EuSoMII: Radiologists, AI must share control of data
November 20, 2017 -- While Hollywood portrays dystopias in which artificial intelligence (AI) has rendered humans obsolete, the truth may not be quite as grim if imaging can harness the power of machine learning, according to research presented on 18 November at the European Society of Medical Imaging Informatics (EuSoMII) meeting in Rotterdam, the Netherlands.  Discuss
BIR: How machine learning can cut false positives
November 7, 2017 -- LONDON - Deep artificial neural networks show comparable sensitivity versus radiologists, and they have great future potential to reduce false positives and patient distress in mammography, a Swiss researcher said on 3 November at the annual congress of the British Institute of Radiology (BIR).  Discuss
Is medical imaging data ready for artificial intelligence?
October 31, 2017 -- Unless you've been shut in a darkened room, you'll have heard about the incoming tsunami of artificial intelligence (AI) algorithms, writes Dr. Hugh Harvey in a special column. But he fears the imaging AI landscape is like the Wild West, and it badly needs a sheriff in town.  Discuss
Why Europeans must care more about AI, machine learning
September 6, 2017 -- In this digital era, new types of businesses related to artificial intelligence (AI) are emerging in several areas of healthcare. Radiologists, in particular, are vulnerable to the growth of automation, write Drs. Sergey Morozov and Erik Ranschaert.  Discuss
Software differentiates ground-glass nodule subtypes
August 1, 2017 -- Lung nodule assessment software can be used to accurately differentiate histological subtypes of lung adenocarcinomas manifesting as ground-glass nodules, helping to reduce diagnostic uncertainty in managing these common lesions, according to Austrian research published online by European Radiology.  Discuss