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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Experts question validation transparency of FDA approved AI devices

Many AI devices have already been integrated into clinical practice, but a new analysis questions whether certain validation processes could lead to algorithm biases.

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AI literacy program earns stamp of approval from radiology residents

Nearly 97% of residents from the nine programs included in this latest research reported a lack of sufficient exposure to AI during their training.

Walgreens changes how it rates its pharmacists

Walgreens has done away with task-based metrics for its retail pharmacy staff, a move that no longer judges pharmacists on how fast they work.

 

FDA greenlights AI-powered MR software that could give radiotherapy planning a boost

The U.S. Food and Drug Administration granted Philips 510(k) clearance for its AI-powered MRI platform tailored to the treatment of head and neck cancers. 

AI-generated coronary tree from a patient's CT scan showing a color code of areas of interest for plaque burden from the Cleerly software shown at SCCT 2022.

VIDEO: The role of AI in cardiac imaging

Ed Nicol, MD, president-elect of the Society of Cardiovascular Computed Tomography, provided us with an exclusive look at how AI is expected to change cardiac imaging.

Man vs. Machine artificial intelligence AI

Should AI-based imaging tools guide treatment decisions?

Abhinhav Jha, PhD, discusses his plans for a $314,807 NIH grant to explore the ethics of AI in imaging given its inherent uncertainties.  

neck ultrasound thyroid

TI-RADS could help guide thyroid nodule biopsy decisions in children

ACR TI-RADS has previously been shown to lack sensitivity for distinguishing between benign and malignant thyroid lesions in pediatric patients.

MRI radiomics could change the future of breast cancer treatment

Radiomics methodologies could change how care plans are managed for patients with breast cancer by identifying those most likely to benefit from specific treatments.