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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An RSNA attendee undergoes an MRI brain scan on the expo floor using the Hyperfine Swoop head MRI system. It is self-shields with a low field 0.064 T. It uses a standard wall power outlet and can be wheeled through a standard 34-inch wide door frame. It weighs 1,400 pounds. Imaging sequences include T1, T2, FLAIR, and DWI (with ADC map) and its operational controls are all directed on an iPad interface. #RSNA #RSNA22

FDA clears new artificial intelligence capabilities for portable MRI scanner

This is the eighth clearance in the past three years for Hyperfine's Swoop system, company officials said Monday. 

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ChatGPT shows ‘tremendous’ potential in simplifying readability of radiology reports

Researchers prompted the large language model to "explain this medical report to a child using simple language" and had rads rate the results based on completeness and correctness. 

GE HealthCare Venue Ultrasound System

GE HealthCare upgrades ultrasound systems with AI guidance

The Venue product line will receive a step-by-step guidance system designed to help even inexperienced operators capture quality cardiac images.

Photos from the study showing eye-tracking and voice dictation.

Eye-tracking study shows radiology reporting via voice commands becoming more viable

When combined with a good microphone, "positive findings only" radiology reporting utilizing voice commands may be most efficient style, according to new research. 

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Clinical decision support has little impact on image-ordering behaviors, single-center study finds

CDS only added 24 seconds to ordering clinicians' workflows and rarely led to these individuals changing their radiology request, experts wrote in JACR. 

AI shows bias based on race and sex

A study calls into question the safety of using popular foundation-model AI applications in a medical setting.

Artificial intelligence (AI) is being developed to help make cardiovascular clinical trials more efficient, lead to faster advances in patient care, and bring possible new treatments to heart patients more quickly. The major cardiac research center of Icahn School of Medicine at Mount Sinai announced today that it signed a memorandum of understanding with the Chiba Institute of Technology (CIT) to collaborate on using AI to enhance cardiovascular disease research.

Mount Sinai partners with the Chiba Institute of Technology on AI to transform cardiovascular research 

Agreement aims to use AI to help make cardiology clinical trials more efficient and lead to faster advances in patient care. 

artificial intelligence

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