Artificial Intelligence

Artificial intelligence (AI) is becoming a crucial component of healthcare to help augment physicians and make them more efficient. In medical imaging, it is helping radiologists more efficiently manage PACS worklists, enable structured reporting, auto detect injuries and diseases, and to pull in relevant prior exams and patient data. In cardiology, AI is helping automate tasks and measurements on imaging and in reporting systems, guides novice echo users to improve imaging and accuracy, and can risk stratify patients. AI includes deep learning algorithms, machine learning, computer-aided detection (CAD) systems, and convolutional neural networks. 

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8 key clinical applications of machine learning in radiology

Artificial intelligence (AI) and machine learning often get lumped together, but as the authors of a new Radiology commentary explained, the two terms are far from interchangeable. While machine learning is a specific field of data science that gives computers the ability to “learn” without being programmed with specific rules, AI is a more comprehensive term used to describe computers performing intelligent functions such as problem solving, planning, language processing and, yes, “learning.”

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Deep learning software reduces variability in cardiovascular imaging

San Francisco-based tech company Bay Labs this week announced the success of its deep learning software, EchoMD AutoEF, in reducing variability in cardiovascular imaging.

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Machine learning tool expedites detection of white matter lesions in stroke patients

A machine learning tool developed by researchers at Imperial College London could assess the severity of leukoaraiosis in stroke patients with greater efficiency and accuracy than the typical emergency room CT, a study published this week in Radiology states.

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Radiologists don’t need to be experts in AI—but they should still study the basics

As the relationship between radiology and artificial intelligence (AI) continues to evolve, radiology trainees may find themselves wondering what, exactly, they should know about these groundbreaking technologies. Do they need to be AI experts? Can they just avoid the subject altogether?

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RSNA announces 2-day course on AI in Paris

RSNA announced this week that it will be offering a new Spotlight Course focused on artificial intelligence (AI) September 23-24 at the Espace Saint-Martin in Paris.

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Lab uses eye-tracking device, AI to study impact of contextual bias on radiologists interpreting mammograms

Radiologists are “significantly influenced” by contextual bias when interpreting mammograms, according to a new study published in the Journal of Medical Imaging.

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Machine learning could enable medical image registration during operations

Researchers from the Massachusetts Institute of Technology (MIT) in Cambridge have been studying a machine learning algorithm they say makes the process of medical image registration more than 1,000 times faster.

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New Zealand imaging provider to use AI for prostate cancer detection

Mercy Radiology, a New Zealand-based imaging provider, has plans to use artificial intelligence (AI) algorithms to help with the detection of prostate cancer.

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