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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Stakeholders gather in London to discuss development of AI in radiology, oncology

Radiologists, clinical oncologists and industry stakeholders gathered May 16 in London to discuss artificial intelligence (AI) in medical imaging and cancer treatment. The all-day event was organized by the Royal College of Radiologists (RCR) with help from the Alan Turing Institute, Health Data Research UK and the Engineering and Physical Sciences Research Council.

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First AI-based medical device gains government approval in South Korea

South Korea’s Ministry of Food and Drug Safety announced this week that, for the very first time, it has approved a medical device that uses artificial intelligence (AI) technology.

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If you think AI will never replace radiologists—you may want to think again

It’s one of the most frequently discussed questions in radiology today: What kind of long-term impact will artificial intelligence (AI) have on radiologists?

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Charles E. Kahn Jr. named editor of RSNA’s new AI journal

Charles E. Kahn Jr., MD, MS, professor and vice chair of the department of radiology at the University of Pennsylvania’s Perelman School of Medicine in Philadelphia, has been named the editor of RSNA’s new online journal, Radiology: Artificial Intelligence.

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Computer algorithms, radiologists evaluate breast density with comparable accuracy

Automated and clinical breast density evaluation methods are equally accurate in predicting a patient’s risk of breast cancer, according to a new study published in Annals of Internal Medicine.

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Deep learning technologies can help radiologists, pathologists provide patients with more value

Anant Madabhushi, PhD, a professor at Case Western Reserve University in Cleveland, has led significant deep learning research in recent years, but he doesn’t necessarily think this evolving technology will replace radiologists and pathologists any time soon.

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ACR, SIIM to host summit focused on AI

The American College of Radiology (ACR) Data Science Institute (DSI) and Society for Imaging Informatics in Medicine (SIIM) are joining forces on May 30 to host the Spring 2018 Data Science Summit: Economics of Artificial Intelligence (AI) in Health Care.

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FDA’s Gottlieb says AI ‘holds enormous promise for the future of medicine’

The FDA is working to encourage the use of artificial intelligence (AI) technologies in healthcare, according the prepared remarks by the agency’s commissioner, Scott Gottlieb, MD, at Health Datapalooza in Washington, D.C.

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