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.

ACR expands programs to help radiology practices integrate and trust AI
CEO Dana Smetherman, MD, MPH, MBA, explains American College of Radiology efforts to help members understand and enable easier integration of artificial intelligence.
Short-term breast cancer risk prediction improves when AI combines imaging with personal info
Understanding which women have the greatest short-term risk could enable providers to implement targeted screening strategies to ensure malignancies are caught at the earliest possible stage.
Healthcare AI today: Oracle reborn with AI, care affordability point/counterpoint, healthcare jobs vs. AI, more
‘If it weren’t for the intransigence of the American Medical Association, we’d be well on our way to fleets of AI doctors diagnosing diseases and prescribing treatments.’
Heart surgeons see more potential in AI than colleagues from other fields
Cardiac surgeons see significant value in AI's ability to assist clinicians with administrative tasks and patient selection. When it comes to making clinical decisions, however, there is still a certain amount of skepticism.
Medicare has denied $16M worth of radiology artificial intelligence claims
The federal payment program first started paying for AI in 2018 and has denied about 53% of claims (or 53,857) submitted by radiologists since then, experts detail in JACR.

Dana Smetherman, MD, MPH, MBA, FACR, chief executive officer of the American College of Radiology (ACR), explains ACR efforts to help members understand and enable easier integration of artificial intelligence (AI) into practice while also ensuring it can be trusted.

ACR expands programs to help radiology practices integrate and trust AI

CEO Dana Smetherman, MD, MPH, MBA, explains American College of Radiology efforts to help members understand and enable easier integration of artificial intelligence.

Breast cancer AI ribbon pink artificial intelligence

Short-term breast cancer risk prediction improves when AI combines imaging with personal info

Understanding which women have the greatest short-term risk could enable providers to implement targeted screening strategies to ensure malignancies are caught at the earliest possible stage.

Healthcare AI today: Oracle reborn with AI, care affordability point/counterpoint, healthcare jobs vs. AI, more

‘If it weren’t for the intransigence of the American Medical Association, we’d be well on our way to fleets of AI doctors diagnosing diseases and prescribing treatments.’

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Heart surgeons see more potential in AI than colleagues from other fields

Cardiac surgeons see significant value in AI's ability to assist clinicians with administrative tasks and patient selection. When it comes to making clinical decisions, however, there is still a certain amount of skepticism.

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Medicare has denied $16M worth of radiology artificial intelligence claims

The federal payment program first started paying for AI in 2018 and has denied about 53% of claims (or 53,857) submitted by radiologists since then, experts detail in JACR.

Practical pointers for using AI in remote patient monitoring

AI software embedded in video devices, wearables and sensors—not to mention actual patient monitors—can continuously track post-surgery patients in real time, sending predictive insights to care teams regardless of where they’re stationed.

FDA clears AI-powered cardiac imaging platform

The Tempus Pixel platform was designed to assist clinicians with the evaluation of cardiac MR images.

Cardiologists have developed an open-source artificial intelligence (AI) model capable of accurately evaluating a long list of measurements on echocardiography results. The group detailed the development and validation of that model in the Journal of the American College of Cardiology.

Open-source AI model delivers accurate echocardiography assessments

The algorithm, trained on more than 150,000 TTE studies, can calculate 18 different measurements regularly used in echocardiography