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.

AI-powered risk model evaluates long-term risk of coronary artery disease
The advanced machine learning model tracks more than 50 different factors to make its predictions. It has already been found to be more accurate than popular prediction methods for heart disease that are currently available.
Enforcement of rule regulating discrimination in AI use will start May 1, ACR warns
However, it’s still uncertain whether the Trump administration will follow through with the new HHS policy update.
Only 4% of women comfortable with AI serving as sole reader of mammograms
“Incorporating patient perspectives into AI implementation strategies ensures that these technologies improve and not hinder patient care," one expert contends.
Most patients trust AI to interpret their imaging, but certain demographic factors shape these opinions
“Incorporating patient perspectives into AI implementation strategies ensures that these technologies improve and not hinder patient care."
AI-based coronary plaque evaluations highlight elevated heart risks in women
“This is the perfect technique to identify high-risk patients who would benefit from intensive therapies,” imaging specialist Gudrun Feuchtner, MD, told Cardiovascular Business.

RSNA 2019 to feature new, larger AI Showcase

RSNA announced Wednesday, July 31, that it would be expanding its AI Showcase at RSNA 2019 in Chicago.

AI boosts accuracy of DBT, slashes radiologists’ reading times

Utilizing an AI system for digital breast tomosynthesis (DBT) can improve radiologists’ accuracy while dramatically reducing reading times, according to a new study published in Radiology: Artificial Intelligence.

Deep learning reads x-rays to prevent mispositioned feeding tubes

A deep learning platform can accurately distinguish critical from non-critical feeding tube placement on radiographs, according to a recent study published in the Journal of Digital Imaging.

Progenics Pharmaceuticals working with VA on AI research program

Progenics Pharmaceuticals, a New York City-based oncology and imaging company, has announced a new collaboration aimed at improving care for veterans with prostate cancer.

Imaging data backs physical activity as guard against Alzheimer’s

Increasing daily physical activity may help older adults delay their progression to Alzheimer’s disease (AD), according to research published July 16 in JAMA Neurology.

AI detects urinary tract stones on CT scans

Convolutional neural networks (CNNS) can detect urinary tract stones on unenhanced CT scans with significant accuracy, according to new findings published in Radiology: Artificial Intelligence.

New AI tool may be a powerful force in cancer care

A deep learning platform created by researchers at the Dana-Farber Cancer Institute can identify cancer in radiology reports as well as clinicians, but in a fraction of the time, according to new research published July 25 in JAMA Oncology.

4D flow MRI offers insight into COPD, emphysema

“Our multicenter study found that 4D flow MRI provided a promising way of measuring blood flow in the superior and inferior caval veins and right heart, which may provide further insight into physiologic and pathologic blood flow patterns in individuals with COPD and emphysema,” wrote researchers in a July 24 Radiology study.

Artificial Intelligence

AI-powered risk model evaluates long-term risk of coronary artery disease

Enforcement of rule regulating discrimination in AI use will start May 1, ACR warns

Only 4% of women comfortable with AI serving as sole reader of mammograms

Most patients trust AI to interpret their imaging, but certain demographic factors shape these opinions

AI-based coronary plaque evaluations highlight elevated heart risks in women