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. 

Multiple sclerosis lesions detected with AI assistance

AI assistance helps rads shave 1/3 of their reporting times for MS lesions

Assessing multiple sclerosis is a time-consuming process, making reducing the burden an interest of multiple AI vendors.

HeartFlow introduced its next generation artificial intelligence (AI) Plaque Analysis with an interactive experience at SCCT 2024. It shows a 3D plaque model and analysis by territory across calcified, non-calcified and low-attenuation plaques. This includes viewing cross-sectional, color-coded images of each plaque type where it was quantified along the vessel. #SCCT #SCCT24 #SCCT2024

Updated HeartFlow technology offers interactive features, full integration with FFR-CT 

HeartFlow is using SCCT 2024 to introduce the world to its updated Plaque Analysis platform. “Accurately diagnosing a patient’s risk for coronary artery disease is critical for determining the best treatment," Chief Medical Officer Campbell Rogers, MD, explained.

lung cancer pulmonary nodule chest

AI shows potential to reduce radiologists’ chest X-ray workload in an outpatient setting

Experts see particular benefit in “situations with high case volumes, which often lead to long work lists and reading delays," according to research published in Academic Radiology

mayo clinic platform

Industry Watcher’s Digest

Buzzworthy developments of the past few days: Mayo Clinic leads the league in AI readiness 

#StanfordHAI #AIregulation Stanford Institute for Human-Centered AI

Workshop consensus: Fixing healthcare AI regulation will take more than tweaks and patches

Querying 55 thought leaders behind closed doors, the Stanford Institute for Human-Centered AI has found only 12% believe healthcare AI should always have a human in the loop.

artificial intelligence in cardiology

Tech companies team up to help cardiologists reach high-risk heart patients

Guidehealth and Story Health are joining forces to put AI-powered technology in the hands of heart teams. 

test exam scantron

Developing board-style radiology questions is resource intensive. Large language models could help

Crafting these materials is typically left up to radiologists who draw from their own educational and clinical experiences, but the process is time consuming and can incur significant costs.

AIRS Medical

Radiology AI firm AIRS Medical raises $20M in Series C financing

The Korean company’s flagship product, SwiftMR, is a deep learning solution that helps providers reduce scan times while maintaining image quality.