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. 

Ed Nicol, MD, consultant cardiologist and honorary senior clinical lecturer with Kings College London and president-elect of the Society of Cardiovascular Computed Tomography (SCCT), explained artificial intelligence (AI) in cardiac CT is here to stay and its use is expanding. He noted that one AI-based algorithm is already included in recent cardiology guidelines and more will likely follow. #SCCT

Cardiac imagers need to understand AI as it enters clinical use and ACC guidelines

Most FDA-cleared AI algorithms are related to radiology and cardiology, meaning radiologists and cardiologists need to make an effort to learn how these technologies work.

artificial intelligence AI deep learning

New AI healthcare challenge offers cash for better outcomes

The Applied AI Healthcare Challenge is looking for diverse and practical solutions that will help federal agencies provide high-quality care.

GE HealthCare acquires AI ultrasound company

The deal will fold Caption Health into GE HealthCare’s $3 billion ultrasound business, supporting the portfolio with AI-enabled imaging.

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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.

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.

Surgeons Operating On Patient

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. 

Around the web

The American College of Cardiology has shared its perspective on new CMS payment policies, highlighting revenue concerns while providing key details for cardiologists and other cardiology professionals. 

As debate simmers over how best to regulate AI, experts continue to offer guidance on where to start, how to proceed and what to emphasize. A new resource models its recommendations on what its authors call the “SETO Loop.”

FDA Commissioner Robert Califf, MD, said the clinical community needs to combat health misinformation at a grassroots level. He warned that patients are immersed in a "sea of misinformation without a compass."

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