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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RadNet and Google Health join forces to use AI for lung cancer screening

Aidence will license, develop, and validate Google Health’s existing AI research module, hoping to offer better differentiation between benign and malignant lung nodules at an early stage.

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New AI model calculates risk of heart attack or stroke using a single X-ray

“This type of screening could be used to identify individuals who would benefit from statin medication but are currently untreated," one specialist said. The full analysis will be presented at RSNA 2022 in Chicago. 

Julius Bogdan, vice president and general manager of the Healthcare Information and Management Systems Society (HIMSS) Digital Health Advisory Team for North America, explains considerations for healthcare system information technology (IT) management teams on the implementation of artificial intelligence (AI). He also discusses ideally how AI should be integrated into medical IT systems, and some of the issues AI presents in the complex environment of real-world patient care." #AI #HIMSS

Radiologist examines AI's potential to transform medical imaging

Linda Moy, MD, the first female editor of Radiology, said that artificial intelligence can help address a multitude of issues today’s radiologists face, but obstacles do remain. 

Charles E. Kahn, Jr., MD, MS, Editor of the the RSNA journal Radiology: Artificial Intelligence, and professor and vice chair of radiology at the University of Pennsylvania Perelman School of Medicine, discusses trends in radiology medical imaging AI. He has been heavily involved in radiology informatics and has seen up close the evolution of radiology toward deeper integration with AI. #RSNA22

VIDEO: An updated look at the use of AI in radiology

Ahead of RSNA 2022 in Chicago, Charles E. Kahn, Jr., MD, MS, spoke with Radiology Business about how AI is being used by radiologists—and how that may evolve in the years ahead.

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The power of AI: Advanced algorithm IDs heart issues using Apple Watch data

A team of Mayo Clinic specialists led the analysis, sharing their findings in Nature Medicine.

Aidoc, Avicenna, Viz.ai and 10 more imaging AI names in the pre-RSNA news

Also worth a look: the ACR Data Science Institute’s AI Central, updated this week with detailed information on imaging AI products that have been cleared by the FDA.

New partnership seeks to streamline AI integration into lung cancer screening

A new partnership between Sirona Medical and RevealDX could streamline the process of AI integration into the clinical practice of lung nodule assessments. 

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Experts ID imaging biomarkers in kids with ADHD

The study's authors explained how MRI results can be used to help identify children with ADHD—and how these findings could be used in the AI algorithms of tomorrow. The team will be presenting its findings at RSNA 2022 in Chicago.