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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4D flow MRI may reduce frequency of endoscopic screening for varices

In patients with liver cirrhosis, four-dimensional (4D) flow MRI can help indicate the risk of bleeding in gastroesophageal varices and reduce the need for invasive endoscopy procedures, wrote authors of an Oct. 16 Radiology study.

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Imaging helps researchers understand brain structure’s impact on language tasks

With the help of diffusion spectrum imaging, scientists from the University at Buffalo in New York are creating models to better understand how brain structure affects language-based performance tasks.

Philips launches first global start-up collaboration program focused on the application of artificial intelligence in healthcare

2-week program gives 19 artificial intelligence start-up companies access to Philips’ health technology expertise and its ecosystem of knowledge partners

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MIT pledges $1B to address the opportunities, challenges of AI

The Massachusetts Institute of Technology (MIT) announced a $1 billion commitment to “address the global opportunities and challenges presented by the prevalence of computing and the rise of artificial intelligence (AI).”

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AI measures breast density as accurately as experienced mammographers

Breast imagers and artificial intelligence (AI) experts have shown that a new AI algorithm measures breast density with accuracy comparable to an experienced breast imager, according to new research published online Oct. 16 in Radiology.

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AI model delivers 'efficient and reliable' breast density assessments

Researchers from Massachusetts General Hospital (MGH) and Harvard Medical School developed a deep learning (DL) model that measures breast density “at the level of an experienced mammographer.” Results of the study were published in Radiology.

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Mixed-reality headset enhances accuracy of external ventricular drain insertion

Using a mixed-reality holographic computer headset, neurosurgeons can more accurately perform external ventricular drain (EVD) insertion, according a new study out of Beijing published in the Journal of Neurosurgery.

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RSNA’s new AI journal names its first deputy editor

William Hsu, PhD, an associate professor of radiological sciences at UCLA, is the first deputy editor of RSNA’s new online journal, Radiology: Artificial Intelligence.