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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NYU’s Daniel Sodickson on AI, Facebook and Why Faster MR Scans Could Improve Healthcare

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A new project is seeking to make MRI scans up to 10 times faster by capturing less data. NYU’s Center for Advanced Imaging Innovation and Research (CAI2R) is working with the Facebook Artificial Intelligence Research group to “train artificial neural networks to recognize the underlying structure of the images to fill in views omitted from the accelerated scan.”

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Machine Learning 101: Simplifying It One Term at a Time

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Machine learning is one of the hottest topics in radiology and all of healthcare, but reading the latest and greatest ML research can be difficult, even for experienced medical professionals. A new analysis written by a team at Northern Ireland’s Belfast City Hospital and published in the American Journal of Roentgenology was written with that very problem in mind.

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Intelligence & Insight: The Latest News in AI and Machine Learning

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A compilation of the latest news in AI and machine learning

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AI distinguishes between low, high-risk prostate cancer on MRI

A multi-institutional team of researchers has developed a new AI learning algorithm that can distinguish between low- and high-risk prostate cancer from multiparametric MRI (mpMRI) scans with higher sensitivity and predictive value than current risk assessment approaches, according to research published online Feb. 7 in the journal Scientific Reports.

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New prediction tool uses AI to help providers treat prostate cancer patients

Researchers have developed a new framework that uses machine learning to predict prostate cancer progression, according to new findings published in Scientific Reports.

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Microsoft announces AI-powered healthcare chatbot

Microsoft unveiled a new tool that allows healthcare organizations to create their own AI-powered chatbots and virtual assistants for various services.

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fMRI identifies brain patterns associated with consciousness

An international group of researchers found evidence of unique patterns of brain activity that may explain the neurological difference between consciousness and unconsciousness, according to a Feb. 6 study published in Science Advances.

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How image analysis competitions can promote faster, more collaborative AI research

In a special report published Jan. 30 in the inaugural issue of Radiology: Artificial Intelligence, Luciano M. Prevedello, MD, and colleagues recognize the challenges of implementing AI into clinical workflows, but also offer potential solutions—specifically image-based competitions—which could foster faster, more collaborative AI research.