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. 

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breast cancer screening mammography

AI accurately predicts breast cancer years before diagnosis

This information could help providers personalize breast cancer screening strategies and initiate treatment earlier.

Left, coronary CT angiography of a vessel showing plaque heavy calcium burden. Right, image showing color code of various types of plaque morphology showing the complexity of these lesions. The right image was processed using the FDA cleared, AI-enabled plaque assessment from Elucid.

FDA clears new software for AI-powered CCTA assessments

Elucid's PlaqueIQ was trained to turn CCTA images into interactive 3D reports that help physicians visualize the presence of atherosclerosis.

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GPT-4 as accurate as neurologists in predicting final diagnosis based on MRI reports

The large language model can also outperform other human providers, radiologists included, new study shows.

Breast arterial calcifications (BACs) identified on screening mammograms may help identify women who face a heightened risk of developing cardiovascular disease (CVD), according to a new analysis published in Clinical Imaging.

Younger women with breast arterial calcifications are at markedly higher risk of major cardiovascular events

Currently, there is no standardized reporting requirement related to BACs, and ACR classifies reporting vascular calcifications on breast imaging as optional. 

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AI implementation improves when radiology staff concerns are considered

Although the potential benefits of artificial intelligence are numerous, its implementation is not without headaches for healthcare staffers. 

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Providing chatbots with guideline context significantly improves their imaging recs

With proper prompts and appropriate context, chatbots can play a valuable role in imaging referrals. 

Deep learning denoising produces quality trauma head CT images at 25% of the radiation dose

Denoising algorithm produces quality trauma head CTs at a fraction of the radiation dose

Radiation doses needed for quality head CT scans in trauma settings can be reduced by as much as 75% using DL-based denoising.

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ChatGPT is 'robbing applicants of their voices' in residency applications

The growing use of ChatGPT on residency applications is prompting concerns over how LLMs might affect the authenticity and value of personal statements in the future.

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'This could be a paradigm shift': How PET with newly approved flurpiridaz compares to SPECT

GE HealthCare's flurpiridaz, the PET radiotracer that recently received FDA approval, offers several key benefits over SPECT. Jamshid Maddahi, MD, discussed the details in an exclusive interview. 

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Ultrafast myocardial contrast echocardiography shows early potential to evaluate CAD

Ultrafast MCE could go on to become a go-to treatment option for obstructive coronary artery disease, according to the authors of a new first-in-human clinical study.

Cardiovascular Business
FDA clears new software for AI-powered CCTA assessments

Elucid's PlaqueIQ was trained to turn CCTA images into interactive 3D reports that help physicians visualize the presence of atherosclerosis.

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