A deep convolutional neural network was able to predict hospital stay, ICU admission and intubation when scoring chest CT images of hospitalized COVID patients.

The new algorithm flags chest x-rays when it detects pneumothorax and notifies physicians of any suspicious findings.

Research published recently in Radiology found comparable sensitivity and specificity between artificial intelligence and clinicians for fracture detection. 

 "This research aims to raise a red flag regarding naive off-label usage of open-access data in the development of machine-learning algorithms," experts involved in the study said.

CTPA is the standard of care for diagnosing PE, but suboptimal scans make it difficult to reach a diagnosis. A new Clinical Imaging study tests the effectiveness of AI when image quality is lacking.

Many decision support tools catered to knee osteoarthritis have emerged in recent years, but external validation that ensures these algorithms can operate in a clinical setting has been lacking.

A study published by Boston University School of Medicine revealed that fracture detection improved for readers by 10.4% with BoneView AI's assistance.

The deep learning model was trained to recognize abnormalities in real-time, reducing delays in image interpretation for clinically relevant findings.