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. 

Thumbnail

VIDEO: Use of AI to address health equity and health consumerization

Julius Bogdan, vice president and general manager of the Healthcare Information and Management Systems Society (HIMSS) Digital Health Advisory Team for North America, explains the use of artificial intelligence (AI) algorithms to help address health disparities and the rise of healthcare consumerism.

Thumbnail

VIDEO: AI can help prevent clinician burnout

Julius Bogdan, vice president and general manager of the Healthcare Information and Management Systems Society (HIMSS) Digital Health Advisory Team for North America, discusses how artificial intelligence (AI) can help combat clinician burnout.

Julius Bogdan, vice president and general manager of the Healthcare Information and Management Systems Society (HIMSS) Digital Health Advisory Team for North America, explains several key artificial intelligence (AI) trends he sees across healthcare.

VIDEO: 9 key areas where AI is being implemented in healthcare

Julius Bogdan, vice president and general manager of the Healthcare Information and Management Systems Society (HIMSS) Digital Health Advisory Team for North America, explains several key artificial intelligence (AI) trends he sees across healthcare.

How AI can boost care for female heart attack patients

Researchers used data from more than 420,000 patients to develop a new AI-powered risk score that could help women receive much better care. 

Automated CT body composition analysis predicts risk of stroke and heart attack

Researchers observed visceral fat area (VFA) measurements derived from abdominal CT scans to be associated with increased cardiovascular risk. 

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. 

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).

Around the web

Ron Blankstein, MD, professor of radiology, Harvard Medical School, explains the use of artificial intelligence to detect heart disease in non-cardiac CT exams.

Eleven medical societies have signed on to a consensus statement aimed at standardizing imaging for suspected cardiovascular infections.