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. 

AI physician leader

Newswatch: AI-eager doctors, AI-reticent buyers, AI cost worriers, more

In medicine’s next chapter, AI literacy will separate physician leaders from peer followers. 

artificial intelligence AI in healthcare

7 pointers for AI-driven quality control in medicine

By automating repetitive tasks and ensuring consistent “QC,” well-deployed AI not only unburdens healthcare professionals but also sets new standards for efficiency and reliability in medical practice. 

artificial intelligence AI heart cardiology

AI-powered risk model evaluates long-term risk of coronary artery disease

The advanced machine learning model tracks more than 50 different factors to make its predictions. It has already been found to be more accurate than popular prediction methods for heart disease that are currently available. 

artificial intelligence

Enforcement of rule regulating discrimination in AI use will start May 1, ACR warns

However, it’s still uncertain whether the Trump administration will follow through with the new HHS policy update. 

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Only 4% of women comfortable with AI serving as sole reader of mammograms

“Incorporating patient perspectives into AI implementation strategies ensures that these technologies improve and not hinder patient care," one expert contends. 

artificial intelligence robot evaluates healthcare data

Most patients trust AI to interpret their imaging, but certain demographic factors shape these opinions

“Incorporating patient perspectives into AI implementation strategies ensures that these technologies improve and not hinder patient care."

Gudrun Feuchtner, MD, MBA, HCM, assistant professor, cardiovascular imaging, Medical University Innsbruck, Department Radiology, explains how artificial intelligence-based quantitative computed tomography (AI QCT) coronary plaque features are better able to predict risk in women, according the the results of the late-breaking CONFIRM2 study at ACC 2025.

AI-based coronary plaque evaluations highlight elevated heart risks in women

“This is the perfect technique to identify high-risk patients who would benefit from intensive therapies,” imaging specialist Gudrun Feuchtner, MD, told Cardiovascular Business.

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ChatGPT effective at simplifying breast imaging recall letters

Emory University radiologists recently sought to improve the readability of their recall messages, asking the large language model for help.