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The Rise of AI in Medical Devices: What It Means for Hiring and Innovation

MRI Network

The number of machine learning- and AI-powered medical devices approved by the U.S. In 2024, the FDA approved nearly 1,000 AI medical devices compared to just 221 in 2023. At the same time, there are concerns about whether the FDA has approved some medical devices too quickly.

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How can Enterprise Imaging empower radiology in the modern health network?

AuntMinnie

With strong demand for medical imaging in many differing clinical contexts, hospitals are managing growing routine imaging demands while balancing teaching practices, ambulatory services, primary care, and subspecialty services. billion healthcare facility. Another, a new hospital complex is underway at University of Utah Health.

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Median highlights clinical trial results for eyonis LCS

AuntMinnie

French imaging software developer Median Technologies is highlighting results from the RELIVE clinical trial regarding its AI-based CADe/CADx software as a medical device for lung cancer screening, eyonis LCS.

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ACR responds to Congressional query on AI reimbursement

AuntMinnie

MD, issued a nine-page letter to Congress recommending how to solve the reimbursement problem for AI in healthcare and ensure clinical AI is of value to patients and health systems. American College of Radiology (ACR) CEO William Thorwarth Jr., As of May 6, the ACR estimated that there are approximately 250 U.S. William Thorwarth Jr.,

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How imaging AI developers can avoid pitfalls when testing algorithms

AuntMinnie

Researchers led by Seyed Tabatabaei, MD, from Massachusetts General Hospital and Harvard Medical School in Boston, in their clinical perspective outlined these pitfalls and made suggestions on AI model training and validation, as well as using diverse datasets.

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AI will transform early cancer detection, save lives in 2025

AuntMinnie

Far from being expendable, human medical experts will remain the linchpin of our healthcare system and the indispensable source of truth whose inputs allow AI models to learn as they go in ways that improve patient health. Researchers are also pairing AI models with specific targeting compounds to help improve diagnostic accuracy.

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AI education is a necessity for newest class of radiologists

AuntMinnie

In healthcare, algorithms hold the promise of increasing efficiency and, potentially, diagnostic accuracy. By investing in AI education, healthcare organizations can empower radiologists to streamline workflows, enhance diagnostic accuracy, and deliver personalized care. Morris Panner, President of Intelerad. The examples are many.

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