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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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.

February 6, 2023
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.

February 6, 2023
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.

February 3, 2023
Tiny fragments of plastic are commonly found deep inside the human body. Heart surgery, it seems, is one of many ways these microplastics are reaching their destination.  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. 

February 3, 2023
New wearable device, no bigger than a stamp, uses AI to deliver on-the-go cardiac imaging

New stamp-sized wearable device uses AI to deliver on-the-go cardiac imaging

The device, designed to be worn for up to 24 hours at a time, uses ultrasound technology and artificial intelligence to track how much blood the user's heart is pumping.

January 26, 2023
As artificial intelligence (AI) adoption expands in radiology, there is growing concern that AI algorithms needs to undergo quality assurance (QA) reviews. How to validate radiology AI? How can you validate medical imaging AI?

Cardiologists use video-based AI model to ID coronary artery disease

A team of specialists out of Cedars-Sinai developed the deep learning model using TTEs from nearly 3,000 patients.

January 26, 2023
Artificial intelligence (AI) has been one of the biggest stories in healthcare for years, but many clinicians still remain unsure about how, exactly, they should be using AI to help their patients. A new analysis in European Heart Journal explored that exact issue, providing cardiology professionals with a step-by-step breakdown of how to get the most out of this potentially game-changing technology.

AI in cardiology: A step-by-step guide to developing high-quality algorithms

Overwhelmed or confused by AI and machine learning technology? A new analysis in European Heart Journal hopes to provide some clarity. 

January 24, 2023
Jakob Weiss, MD, a radiologist affiliated with the Cardiovascular Imaging Research Center at Massachusetts General Hospital and the AI in Medicine program at the Brigham and Women’s Hospital in Boston, helped develop an deep learning AI algorithm that can assess a patient's biological age and risk assess patients for various diseases. #RSNA #AI #ImagingAI

VIDEO: AI predicts heart disease risk using single chest X-ray

Jakob Weiss, MD, was the lead author on a study that used AI to determine a patient's cardiovascular risks based on a standard chest X-ray.

January 12, 2023
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