Jha S and Topol EJ. Adapting to Artificial Intelligence: Radiologists and Pathologists as Information Specialists. JAMA 2016; 316(22): 2353-2354. Click here to view the paper Abstract Artificial intelligence—the mimicking of human cognition by computers—was once a fable in science fiction but is bec
COVID-19 pandemic has turned the world upside down and the field of radiology is not immune. How has radiology changed? Are you prepared for what the future might hold? Learn how radiologists as individuals, radiology as a field, and emerging technologies will all need to adapt to a changing healthc
As the anti-racism protests continued across the US and people are turning their Instagram posts pitch black today to stand in solidarity with those who are fighting against racial injustice. It’s a strong reminder that no one should take racial harmony for granted and diversity should always be a t
Anthony Chang in conversation with Sebastien Ourselin of King’s College London and Craig Rhodes of NVIDIA about MONAI: an open-source AI framework for healthcare which measures the quality of medical imaging tools by providing domain-specific data transforms, neural network architectures and evalua
Dr. Rizwan Malik, Clinical Lead for Radiology at the Royal Bolton Hospital in UK planned to test qXR, an artificial intelligence (AI) driven chest x-ray system developed by Qure.ai, a company based in Mumbai, India, when he noticed some of his patients needed to wait long hours for a specialist to e
The COVID-19 pandemic is running its apocalyptic course around the world. One thing is certain in the midst of total uncertainty and utter chaos: SARS-CoV-2 is a very daunting enemy and we remain totally subjugated by these viral overlords. It is easy, therefore, for we humans to lose patience and b
Dr Anthony Chang, Founder, AIMed speaks with Dr Geraldine McGinty, President, American College of Radiology, Departments of Radiology and Population Science, Weill Cornell Medicine. Hear more from Geraldine at AIMed Radiology part of our #clinicianseries next week.
Hosny A, Parmar C, Quackenbush J et al. Artificial Intelligence in Radiology. Nat Rev Cancer 2018; 18(8): 500-510. Click here to view the paper Abstract Artificial intelligence (AI) algorithms, particularly deep learning, have demonstrated remarkable progress in image-recognition tasks. Methods rang
Greenspan H, van Ginneken B, and Summers RM. Guest Editorial/Deep Learning in Medical Imaging: Overview and Future Promise of an Exciting New Technique. IEEE Transactions on Medical Imaging 2016; 35(5): 1153-1159. Click here to view the paper DEEP learning is a growing trend in general data analysi