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For patients with newly diagnosed obstructive coronary artery disease (CAD), a multimodal machine learning model offered an 86 percent AUC for predicting MACE, which was 10 percent higher than CCTA alone and over 35 percent higher than the Framingham Risk Score.

Drs. Charles Liu and Jonathan Russin discuss the benefits and potential of fPACT, the alternative to functional MRI.

Emerging research suggests that a deep learning model may offer 92 percent sensitivity in lung tumor detection on CT scans and up to a 59 percent reduction in tumor segmentation time.

In this podcast episode, Dr. Shalom Kalnicki, from Montefiore and Albert Einstein College of Medicine, discusses the disparities minority patients face with cancer screenings and what can be done to increase access during the pandemic.

In computed tomography (CT) scans for patients with solid non-small cell lung cancer (NSCLC) < 30 mm, emerging research suggests the lollipop sign is associated with a greater than fourfold likelihood of angiolymphatic invasion.

The IQ-UIP AI software may bolster computed tomography diagnosis of usual interstitial pneumonia (UIP), which is reportedly misdiagnosed in over 50 percent of cases.