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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RSNA launches new journal focused on AI in radiology

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

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fMRI reveals a lack of sleep increases sensitivity to pain

A team of U.S. researchers used fMRI to discover that a lack of sleep can reduce the brain's ability to combat pain, according to a Jan. 28 study published in the journal JNeurosci.

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Stanford researchers release large chest x-ray dataset to train AI models

Researchers from Stanford University in California have published a large, public dataset containing more than 224,000 chest x-rays from more than 65,000 patients to train AI algorithms. The team also announced a competition inviting developers to submit their chest x-ray interpretation models to detect pathologies more accurately than certified radiologists. 

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NIH-backed study identifies brain biomarkers tied to severe PTSD

Using fMRI, a team of researchers discovered combat veterans with severe post-traumatic stress disorder (PTSD) demonstrate distinct patterns in how their brain and body respond to learning danger and safety. The study may help explain why some experience more severe symptoms than others.

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Novel 3D imaging tool captures blood flow in the capillaries

Researchers at Northwestern University in Evanston, Illinois have developed a noninvasive, three-dimensional (3D) imaging tool able to capture blood flow and oxygenation within the capillaries of a human, according to research published in the journal Light: Science & Applications. The technique could help detect conditions from headaches to cardiovascular disease, sooner.

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Virginia Tech researchers use brain imaging, AI to diagnose mental illness

In an effort to destigmatize mental illness and help patients find better treatments, researchers from Virginia Tech’s Fralin Biomedical Research Institute in Roanoke, Virginia trained a machine learning algorithm with brain fMRI scans to diagnosis mental disorders more accurately than standard methods, according to a recent report by The Verge.

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Is AI keeping medical students from pursuing a career in radiology?

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.

Radiologists unwilling to understand AI are hindering future students

“Students rely on us to understand how radiology is incorporating new technology and what the future of the field will look like for them, but many of us are ill prepared to teach the younger generation about this, mostly because we ourselves are not sure,” Allison Grayev, MD, wrote in an editorial published in Academic Radiology.