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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AI studies can be confusing, even for imaging professionals—but they don't have to be

Machine learning (ML) has become 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 published in the American Journal of Roentgenology was written with that very problem in mind.

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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 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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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.

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Stronger together: AI performs better with radiologist input

Artificial intelligence (AI) algorithms perform significantly better when they include the opinions of radiologists, according to a new study published in the Journal of the American College of Radiology.

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Google’s AI algorithm for detecting breast cancer put to the test in 2 new studies

An artificial intelligence (AI) algorithm developed by Google can help detect metastatic breast cancers with significant accuracy and improve pathologist performance, according to two new studies published in the Archives of Pathology and Laboratory Medicine and the American Journal of Surgical Pathology.

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AI distinguishes false-positive mammograms from malignant, negative mammograms

Artificial intelligence (AI) can help radiologists distinguish false-positive mammograms from malignant and negative mammograms, according to new research published in Clinical Cancer Research.

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ESR and GE Healthcare announce AI partnership for ECR 2019

The European Society of Radiology (ESR) and GE Healthcare have announced a new partnership focused on artificial intelligence (AI) for the European Congress of Radiology (ECR) 2019 in Vienna, Austria. 

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FDA-cleared software increases throughput for flurpiridaz back-to-back rest-stress imaging

The new F-18 flurpiridaz radiotracer is expected to help drive cardiac PET growth, but it requires waiting between rest and stress scans. Software from MultiFunctional Imaging can help care teams combat that problem.

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MRI projectile incident likely to result in a 'seven-figure sum' repair bill for hospital

News of an incident is a stark reminder that healthcare workers and patients aren’t the only ones who need to be aware around MRI suites.

Health Imaging
American College of Radiology announces significant expansion of Lung Cancer Screening Registry

The ACR hopes these changes, including the addition of diagnostic performance feedback, will help reduce the number of patients with incidental nodules lost to follow-up each year.