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Adjunctive AI Powered Tool for Tuberculosis Detection Gets FDA's Breakthrough Device Designation
With reported increases in tuberculosis cases after the COVID-19 pandemic, the qSpot-TB adjunctive artificial intelligence (AI) device may facilitate improved diagnosis of the disease on chest X-rays.
The Food and Drug Administration (FDA) has granted breakthrough device designation to qSpot-TB, an artificial intelligence (AI)-powered device, which may enhance tuberlosis (TB) detection on chest X-rays.
Qure.ai, the developer of qSpot-TB, said the device localizes signs of TB on chest X-rays and provides a conclusion of whether TB is present or not.
The emergence of the qSpot-TB device is particularly timely, according to the company, given statistics from the Centers for Disease Control and Prevention (CDC) showing 8,300 reported TB cases in 2022.
The qSpot-TB device, which recently garnered a breakthrough device designation from the FDA, localizes signs of TB on chest X-rays, and provides a conclusion of whether TB is present or not, according to Qure.ai, the developer of qSpot-TB. (Image courtesy of Qure.ai)
"The increase in TB cases in USA is a reminder about the importance of collective global efforts to continue the fight against the disease until eliminated. We cannot let our guard down. Innovative technology is a crucial component for accelerated progress to successfully end TB globally,” said Professor Kenneth G. Castro, M.D., a co-director of the Emory Tuberculosis Center, and professor of global health, epidemiology, and infectious disease with the Rollins School of Public Health at Emory University.
Study Assesses Lung CT-Based AI Models for Predicting Interstitial Lung Abnormality
September 6th 2024A machine-learning-based model demonstrated an 87 percent area under the curve and a 90 percent specificity rate for predicting interstitial lung abnormality on CT scans, according to new research.
What a Prospective CT Study Reveals About Adjunctive AI for Triage of Intracranial Hemorrhages
September 4th 2024Adjunctive AI showed no difference in accuracy than unassisted radiologists for intracranial hemorrhage (ICH) detection and had a slightly longer mean report turnaround time for ICH-positive cases, according to newly published prospective research.
FDA Expands Clearance of MRI-Guided AI Platform for Deep Brain Stimulation and Lesioning Techniques
September 3rd 2024Utilizing a new machine learning model, the OptimMRI software may improve radiosurgery applications and lesioning techniques such as MRI-guided focused ultrasound through enhanced targeting of the inferolateral part of the ventral intermediate nucleus (VIM).
