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. 

Thumbnail

AI, radiomics predict prostate cancer aggressiveness from MRIs

“Assessing (prostate cancer) PCa invasiveness as early as possible is essential for disease management, treatment choice, and patient prognosis,” wrote the authors of a new study published in Clinical Radiology.

Thumbnail

New MRI method shows molecular changes in the brain

A new MRI technique out of the Hebrew University of Jerusalem (HUJI) can show the molecular makeup of the brain, potentially helping clinicians diagnose neurodegenerative diseases such as Alzheimer’s.

Thumbnail

3 things to know about AI’s upcoming impact on radiology

AI is central to many large technology companies such as Facebook and Google, and may soon have a similar role in the medical imaging world, argued a group of radiologists in a new editorial published in Clinical Imaging.

Thumbnail

How AI can predict fatal heart attacks years in advance

New AI-based technology can identify patients at risk of a deadly heart attack years before it happens, according to new findings published in the European Heart Journal.

Thumbnail

Can MR images of dogs offer insights into human brains?

Why do some dogs hunt while others herd? The connection between brain structure and function is well-known in both humans and canines, but new research published in the Journal Neuroscience offers new insight into the relationship between innate brain wiring and learned behavior.

Thumbnail

AI built on CCTA images can predict heart attacks

Researchers from the University of Oxford have created a new biomarker based off of coronary CT angiography (CCTA) images that can select patients at a high risk of heart attack five years before they occur.

Thumbnail

AI chatbots have a future in healthcare, with caveats

Healthcare consumers are open to interacting with AI chatbots as long as the interaction involves general health information, not patient-specific advice or results from exams.

Thumbnail

AI uses imaging findings to predict presence of thyroid nodules

Machine learning models can be trained to extract immunohistochemical (IHC) characteristics from the imaging results of patients with suspected thyroid nodules, according to new research published in the American Journal of Roentgenology.