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. 

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?

AI-powered triage software for mammograms gains FDA clearance

CureMetrix, a La Jolla, California-based healthcare technology company, has received FDA clearance for its new AI-based triage software solution for mammography.

March 25, 2019

AI trained on more than 1M medical images accurately detects breast cancer

Researchers have developed a new convolutional neural network (CNN) that can predict the presence of breast cancer with the accuracy of an experienced radiologist. 

March 22, 2019
Quantitative imaging and lung cancer

AI predicts how NSCLC patients will respond to chemotherapy

Artificial intelligence and radiomics can help specialists predict how patients with non–small cell lung cancer (NSCLC) will respond to chemotherapy, according to new research published in Radiology: Artificial Intelligence.

March 21, 2019
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?

5 key takeaways from a patient survey about AI in radiology

What do patients think about the use of artificial intelligence (AI) in radiology? A new study published in the Journal of the American College of Radiology addressed that very question.

March 15, 2019

Book on AI highlights radiology’s new role

Deep Medicine, a new book from cardiologist Eric Topol, MD, explores the evolving relationship between artificial intelligence (AI) and healthcare. The New York Times interviewed Topol about the book, and AI’s impact on radiology was one of the first topics that came up.

March 13, 2019

Most AI research focused on radiology lacks external validation

Most researchers exploring the performance of artificial intelligence (AI) in radiology aren’t validating their results, according to a new study published by the Korean Journal of Radiology.

March 11, 2019

AI detects breast cancer as well as most radiologists

Artificial intelligence (AI) systems can achieve a cancer detection accuracy similar to that of an average breast radiologist, according to new findings published by the Journal of the National Cancer Institute.

March 6, 2019

Verily, Google launch AI-powered screening program for eye disease

Verily and Google have launched a new program that brings machine learning-powered screening for two diabetic eye diseases to patients in India.

March 4, 2019

Around the web

"This was an unneeded burden, which was solely adding to the administrative hassles of medicine," said American Society of Nuclear Cardiology President Larry Phillips.

SCAI and four other major healthcare organizations signed a joint letter in support of intravascular ultrasound. 

The newly approved AI models are designed to improve the detection of pulmonary embolisms and strokes in patients who undergo CT scans.

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