AI

Siamese neural network can predict intubation and which patients were likely to die within three days of hospital admission.

Avicenna.AI’s CINA Head earns 510(k) clearance for emergency room triage of intracranial hemorrhages and large vessel occlusions.

Artificial intelligence tools have many drawbacks and face many barriers to clinical implementation, and radiologists must pay close attention to how – and what kind of – data is used in models.

Quantib AI Node is designed for more rapid processing of CT and MRI scans.

One expert makes the case that the negative hype around artificial intelligence is not warranted and the radiologist’s role is secure.

Rapid ASPECTS receives clearance as first neuroimaging analysis device in computer-aided diagnostic category.

ACR and RSNA leaders request the FDA slow its momentum with AI tools that work without radiologist oversight.

510(k) clearance applies to four critical abnormalities; two are exclusive to Qure.ai’s product.

Convolutional neural network accurately identifies “mass effect” lesions in more than 50 disease entities.

The industry should pay more attention to the interplay between providers and AI tools, says Elizabeth Krupinski, Ph.D., during SIIM 2020.

Deep learning algorithm is more accurate in predicting which patients with knee osteoarthritis might need a total knee replacement.

New artificial intelligence system can detect eight abnormalities, potentially facilitating radiology reporting, diagnosis, and treatment.

Radiologists must engage in social media messaging to regain control of information about AI use in diagnostic imaging.

Diagnostic Imaging's Weekly Scan: June 19, 2020

AI model can help alleviate increased sonographer workload, but still has high missed diagnosis rate.

Johns Hopkins Medicine researchers see “untapped potential” for artificial intelligence tools.

Software supports CT and X-ray chest imaging.

Model could help detect the virus, isolate patients, and prevent disease spread.

Algorithms can create errors in multiple imaging systems, according to new tests.

AI-guided imaging supports assessment of cardiac function and reduces personnel COVID-19 exposure.

Deep-learning model outperformed neuroradiologists in predicting risk for disease development.

Tool pinpoints incidental findings on CT scans that contain the lung or part of the lung.

Diagnostic Imaging Weekly Scan -- May 1, 2020

Adding AI to manual reads improves accuracy, specificity, and sensitivity.

An artificial intelligence algorithm uses 3D MRI images to identify a specific genetic mutation that prompts tumor development.

Dr. Eliot Siegel discusses benefits, cautions, and long-term impact of using AI imaging tools during the outbreak.

Dr. Eliot Siegel discusses the role these tools play, as well as the challenges radiologists could encounter with using them.

Using AI technologies when imaging isn’t recommended for detection offers little benefit, according to an industry expert.

Radiology must have a plan for implementing the growing number of AI algorithms.  

XRAIT tool finds more broken bones than X-Rays or CT scans of this population.