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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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.

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Biological ‘brain age’ could help pave the way for more personalized medicine

AI-powered analysis can now assess cognitive decline by noting gaps in chronological versus biological “brain age.”

Emerging imaging technologies boosted by COVID research

As the field of radiology research adapted to withstand the pandemic’s challenges, it morphed in some decidedly beneficial ways.

York University researchers demonstrate how AI can help predict brain metastasis outcomes

AI bests humans at predicting outcomes for brain radiotherapy patients

The new technology could help develop more tailored treatment plans. 

An overview of artificial intelligence (AI) in radiology with Keith Dreyer with the ACR. Images shows a COVID-19 lung CT scan reconstruction from Siemens Healthineers. #AI #radAI #ACR

AI triages pneumothorax patients with differentiated diagnoses

A commercially available AI package has proven adept at distinguishing between two closely similar but unequally urgent conditions on chest X-rays.

RadNet subsidiary gets green light for breast density AI

The FDA has cleared software that automatically assesses density of breast tissue on mammography.

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.

VIDEO: Radiology AI aids acute care and other departments

Sanjay Parekh, PhD, senior market analyst with Signify Research, explains how some radiology AI is being adopted outside of radiology departments to improve care.

Example of AI automated detection and highlighting of critical lung findings on a chest X-ray for a possible lung cancer nodule and fibrosis. Example shown by AI vendor Lunit.

VIDEO: Radiology AI trends at RSNA 2022

Sanjay Parekh, PhD, senior market analyst with Signify Research, discusses trends in radiology AI seen on the expo floor and in sessions at RSNA 2022.

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