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. 

Ischemic stroke shown in CT scans. Image courtesy of RSNA

VIDEO: AI for stroke detection on CT imaging

Bibb Allen, MD, FACR, chief medical officer of the American College of Radiology (ACR) Data Science Institute, explains the trend of using AI for the automated detection of stroke on computed tomography (CT) imaging and the need to include radiologists on the stroke care team.

ESC Congress 2022 European Society of Cardiology

6 key sessions from ESC Congress 2022: TAVR mortality, AI vs. sonographers, radial vs. femoral access and more

ESC Congress 2022, the annual meeting of the European Society of Cardiology, was jam-packed with eye-opening new research from many of the leading voices in cardiovascular and vascular medicine. These six sessions were just some of the weekend's many highlights. 

Dyad Medical Echo:Prio FDA

Regulatory Roundup: FDA approves new-look self-expanding stent, clears 2 advanced AI models

The FDA has had a busy month, overseeing the recall of nearly 88,000 implantable cardiac devices, juggling the continued rise of monkeypox cases in the United States and maintaining an active Breakthrough Devices program. This rundown covers some of the agency's biggest moves during that time. 

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InterWell Health completes $2.4B three-way merger with Fresenius, Cricket Health

InterWell Health has completed its merger with Fresenius Health Partners and Cricket Health in a deal valued at $2.4 billion. The three-way merger was originally announced in March 2022

women burnout

AI model explores EHR data to predict physician burnout

A new AI tool from Washington University in St. Louis researchers aims to help identify burnout among physicians and could potentially prevent it in the future.

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AI identifies Parkinson’s from breathing patterns

The tool could help alleviate the disease onset gap between when symptoms of Parkinson’s first appear and when most people receive a diagnosis.

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

VIDEO: How hospital IT teams should manage implementation of AI algorithms

Julius Bogdan, vice president and general manager of the HIMSS Digital Health Advisory Team for North America, explains considerations for healthcare IT teams on the implementation of artificial intelligence (AI).

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Concerns raised over how hospitals can validate radiology AI algorithms

As artificial intelligence (AI) adoption expands in radiology, there is growing concern that AI algorithms need to undergo quality assurance (QA) reviews.

Around the web

Compensation for heart specialists continues to climb. What does this say about cardiology as a whole? Could private equity's rising influence bring about change? We spoke to MedAxiom CEO Jerry Blackwell, MD, MBA, a veteran cardiologist himself, to learn more.

The American College of Cardiology has shared its perspective on new CMS payment policies, highlighting revenue concerns while providing key details for cardiologists and other cardiology professionals. 

As debate simmers over how best to regulate AI, experts continue to offer guidance on where to start, how to proceed and what to emphasize. A new resource models its recommendations on what its authors call the “SETO Loop.”