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How imaging AI developers can avoid pitfalls when testing algorithms

AuntMinnie

The radiologist made a correct interpretation upon assessment of the entire exam. Successful clinical deployment of AI tools requires that radiologist end-users understand such pitfalls along with other limitations of the available models,” they wrote. The AI algorithm interpreted the finding as a rib fracture. (B)

Imaging 105
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ISCT: AI continues surge into CT imaging

AuntMinnie

In his talk, Rajiv Gupta, MD, PhD, from Massachusetts General Hospital outlined the state of AI in medical imaging and for CT specialists. He said that AI allows radiologists to view what they cannot see with the naked eye. The number of AI-based medical devices cleared by the U.S.

Imaging 53
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The Role of 3D Printing in Radiology

Vesta Teleradiology

That’s why we, as radiologists, are so well positioned to be at the center of these workflows. We can use our deep understanding of imaging modalities, anatomy, and disease to create models, interpret findings and also to know the limitations of the images, and communicate with other providers.”

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GE HealthCare to Spotlight Industry-Leading AI-Enabled Portfolio and Digital Solutions at HIMSS 2024

Imaging Technology

milla1cf Thu, 03/07/2024 - 20:10 March 7, 2024 — GE HealthCare will showcase its industry-leading portfolio of artificial intelligence ( AI )-enabled medical devices and digital solutions in Booth 2500 at the Health Information and Management Systems Society ( HIMSS ) Global Health Conference and Exhibition in Orlando, FL from March 11-15, 2024.

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Why Enterprise-Wide AI Requires Image- and Report-Based AI

Aidoc

Since AI has found its place in the workflows of radiologists , the novel technology continues to expand to other hospital service lines, increasing its potential to impact workflows beyond the reading room. Aidoc manufactures medical and non-medical devices. Report-based AI : Natural language processing (NLP) driven AI.

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AI in Healthcare: The Ultimate Guide

Aidoc

Over 700 devices are categorized as “artificial intelligence and machine learning enabled medical devices” on the FDA website. Healthcare examples : Chatbots for billing and scheduling or filtering and organizing data within a medical device, such as an MRI or CT scanner.

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The Future of Radiology with 5G

Vesta Teleradiology

Patients who need appointments or images read by medical professionals are able to receive the care they need through telehealth services and remarkably clearer images. In addition to this, 5G technology has helped remotely train the practitioners, who were not radiologists , to take the ultrasound examinations.