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. 

RSS icon
artificial intelligence robot evaluates healthcare data

FDA grants breakthrough designation for new AI model to detect cardiac amyloidosis in ECG results

Anumana, Pfizer and Mayo Clinic all worked together to develop the advanced algorithm. The groups are now targeting full regulatory approval in the U.S., Europe and Japan.

Artificial intelligence automated measurements on an echocardiogram on the Siemens SyngoDynamics cardiovascular imaging and information solution. AI is helping speed workflows and complete tedious tasks faster and more accurately that humans, allowing sonographers and cardiologists to be more efficient. Photo by Dave Fornell

AI technologies to be featured heavily at ASE 2023

Artificial intelligence will be one of the hottest topics at the upcoming American Society of Echocardiography meeting in National Harbor, Maryland. 

artificial intelligence robot evaluates healthcare data

Many medical students believe AI poses a threat to the radiology job market

While radiologists and current trainees are either prepared to or are already embracing artificial intelligence, a significant portion of medical students shy away from radiology because of AI.

artificial intelligence healthcare industry news

Industry Watcher’s Digest

Buzzworthy developments of the past few days.

ChatGPT excels at differential diagnostics in hard cases

Today’s generative AI—namely ChatGPT-4—is pretty darned good at parsing out probable diseases in difficult-to-diagnose patient cases.

A figure from the study shows a chest radiograph with an area of consolidation involving right lower lung consistent with pneumonia, as well as right pleural effusion. The deep-learning model predicted risk of 30-day mortality of 9%. Right: Gradient- weighted class activation map shows that model prediction was influenced by separate area of image corresponding with heart and liver (yellow and light blue colors). Patient’s CURB-65 score was 4. Patient recovered from pneumonia and remained alive. AJR Image

Deep learning predicts pneumonia mortality on chest X-rays

AI was able to predict 30-day mortality risk predictions more accurately that the current risk assessment.

ChatGPT large language AI radiology patient information

Society of Interventional Radiology bests ChatGPT at informing patients—but contest reveals shortcomings on both sides

As a source of patient information, human-authored SIRweb.org beats ChatGPT on readability and, in a word, helpfulness. However, the website needs work on those scores too.

artificial intelligence industry digest

Industry Watcher’s Digest

Buzzworthy developments of the past few days.

Displaying 689 - 696 of 2555
Design by Adaptive Theme