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. 

GPT-4 confidently struggles on radiology exam

Image-based questions were significantly more challenging for the large language model to answer, despite the latest version now being capable of accepting image prompts.

April 26, 2024
Sarah Jane Rinehart, MD, director of cardiac imaging, Charleston Area Medical Center, Charleston West Virginia, as been using the FDA-cleared RoadMap artificial intelligence algorithm from HeartFlow in studies and in clinical used since it was cleared and said it helps cardiologists in several ways. #ACC #ACC24 #ACC2024 #Heartflow #AIhealth

AI improves CT assessments, boosts care for real-world heart patients

Automated AI-generated measurements combined with annotated CT images can improve treatment planning and help referring physicians and patients better understand their disease, explained Sarah Jane Rinehart, MD, director of cardiac imaging with Charleston Area Medical Center.

April 26, 2024
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Natural language processing spots reporting gaps, racial bias

Finding such discrepancies is critical to the continuity of patient care, as medical records and reports are often utilized across multiple providers and facilities. 

April 24, 2024
The imaging iodine contrast shortage is delaying procedures and causing rationing at hospitals. impact is it having on hospitals and the tough decisions that are being made to triage patients to determine if they will get a contrast CT scan or an interventional or surgical procedure requiring contrast. Photo by Dave Fornell

ChatGPT shows 'significant promise' in guiding contrast-related decisions

This could be especially helpful when timely clinical decisions relative to the use of a contrast agent need to be made.

April 23, 2024
Advanced artificial intelligence (AI) models can evaluate cardiovascular risk in routine chest CT scans without contrast, according to new research published in Nature Communications.[1] In fact, the authors noted, the AI approach may be more effective at identifying issues than relying on guidance from radiologists. Representative non-contrast CT slices for two patients (left), with super-imposed segmentations (right). One artificial intelligence (AI) model was used to segment a cardiac mask.

AI predicts cardiovascular risk during CT scans—no invasive tests or contrast required

Two advanced algorithms—one for CAC scores and another for segmenting cardiac chamber volumes—outperformed radiologists when assessing low-dose chest CT scans. 

April 23, 2024
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Even AI struggles to work under stress, study suggests

Apparently, it isn’t just humans who occasionally struggle to work under stress. According to a recent study, the performance of AI flounders, too. 

April 18, 2024
chatgpt for patient questions about radiology

ChatGPT both passes and fails at translating free-text into structured reports

While the latest ChatGPT models show promise in easing the reporting burden on radiologists in the future, they aren't up to the task just yet.

April 17, 2024
ChatGPT large language models radiology health care

GPT-4 spots radiology report errors in less time, at a lower cost

The large language model can identify report errors seven times more quickly than human readers, new study reveals.

April 16, 2024

Around the web

Automated AI-generated measurements combined with annotated CT images can improve treatment planning and help referring physicians and patients better understand their disease, explained Sarah Jane Rinehart, MD, director of cardiac imaging with Charleston Area Medical Center.

Two advanced algorithms—one for CAC scores and another for segmenting cardiac chamber volumes—outperformed radiologists when assessing low-dose chest CT scans. 

"Gen AI can help tackle repetitive tasks and provide insights into massive datasets, saving valuable time," Thomas Kurian, CEO of Google Cloud, said Tuesday. 

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