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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A busy week for cardiology investments: 3 tech companies report big financing rounds

It’s not even Valentine’s Day yet, but February has already been a big month for fundraising in the cardiology space.

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Cardiologists ask popular AI model ChatGPT to answer questions about cardiology

Can ChatGPT discuss preventive cardiology with patients? Cardiologists with Cleveland Clinic and Stanford University put the popular AI model to the test, sharing their findings in JAMA.

DiA Imaging Analysis, an Israel-based healthcare technology company, has gained U.S. Food and Drug Administration (FDA) clearance for LVivo IQS, a new software solution designed to help users acquire high-quality echocardiography images.

FDA clears new AI-powered cardiac imaging solution

The newly approved software uses artificial intelligence to provide users with real-time feedback related to image quality.

An example of artificial intelligence (AI) automated detection of a intracranial hemorrhage (ICH) in. a CT scan used to send alerts to the stroke acute care team before a radiologist even sees the exam. Example shown by TeraRecon at RSNA 2022.

FDA has now cleared more than 500 healthcare AI algorithms

More than 500 clinical AI algorithms have now been cleared by the FDA, with the majority just in the past couple years.

An example of an FDA cleared radiology AI algorithm to automatically take a cardiac CT scan and identify, contour and quantify soft plaque in the coronary arteries. The Cleerly software then generates an automated report with images, measurements and a risk assessment for the patient. This type of quantification is too time consuming and complex for human readers to bother with, but AI assisted reports like this may become a new normal over the next decade. Example from Cleerly Imaging at SCCT 2022.

Legal considerations for artificial intelligence in radiology and cardiology

There are now more than 520 FDA-cleared AI algorithms and the majority are for radiology and cardiology, raising the question of who is liable if the AI gets something wrong.

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AI model predicts risk of post-operative AFib

Post-operative atrial fibrillation was once viewed as a fairly insignificant issue, but more recent research suggests it can increase a patient’s risk of multiple adverse events. 

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AI program ChatGPT now has a published article in Radiology—is it any good?

The human author reviewing the article wrote about the benefits and inherent risks of utilizing AI in a medical publication setting, concluding that, overall, it could be “a powerful tool” used in the future of medical publishing—when used with caution.

Brent Savoie, MD, JD, vice chair for radiology informatics, section chief of cardiovascular imaging, Vanderbilt University, explains who will get sued when there is a misdiagnosis due to artificial intelligence (AI).

VIDEO: Who gets sued when radiology AI fails?

Brent Savoie, MD, JD, vice chair for radiology informatics, section chief of cardiovascular imaging, Vanderbilt University, explains who will get sued when there is a misdiagnosis due to artificial intelligence (AI).

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