We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress hp
Sign In
Advertise with Us

Download Mobile App




AI-Enabled Chest X-Ray Solution Elevates ICU and ER Care Pathways

By MedImaging International staff writers
Posted on 14 Sep 2023
Image: The qXR AI-enabled chest X-ray solution has received 510(k) FDA clearance under two critical findings (Photo courtesy of Qure.ai)
Image: The qXR AI-enabled chest X-ray solution has received 510(k) FDA clearance under two critical findings (Photo courtesy of Qure.ai)

Pneumothorax (PTX), a condition where air collects in the pleural space and causes lung collapse, and pleura effusion (PE) in which fluid accumulates in the pleural cavity, create serious challenges in emergency rooms and intensive care units (ICUs). Now, an AI-enabled chest X-ray solution has received 510(k) FDA clearance to triage PTX and PE.

Qure.ai (Mumbai, MH, India) has secured 510(k) FDA clearance for its artificial intelligence-powered chest X-ray solution, known as qXR, specifically for the rapid identification of PTX and PE. This new clearance adds to the company's existing FDA-approved product range, which includes solutions like qXR-BT for breathing tube positioning, qER for emergency room head CT scans, and qER-Quant for head CT quantification software. qXR is designed to integrate seamlessly into current healthcare pathways, enhancing both ICU and ER operational efficiency. Clinical evaluations of qXR's effectiveness in identifying PTX have demonstrated outstanding accuracy in providing rapid passive notifications that take an average of just 10 seconds to reach healthcare staff.

Such rapid alerting capabilities make qXR-PTX-PE an invaluable asset for timely medical decision-making, particularly in critical settings like ICUs and emergency departments. The technology employs a training dataset gathered from multiple global sources and fits seamlessly into the current standard healthcare protocols, acting as a passive notification system for prioritizing tasks. A multi-center study assessing overlooked and incorrectly labeled chest X-ray findings for conditions like PTX and PE showed that the qXR algorithm achieved up to 96% sensitivity and 100% specificity.

“Speaking to physicians and hospital CEOs, we have heard the increasing need to reduce time to diagnosis." said Prashant Warier, CEO and Co-Founder of Qure. The FDA clearance of the qXR algorithm further demonstrates Qure’s commitment to addressing these challenges by optimizing healthcare delivery in time-sensitive settings like the ICU and ER.”

Related Links:
Qure.ai 

Biopsy Software
Affirm® Contrast
Mobile X-Ray System
K4W
Half Apron
Demi
Digital Radiographic System
OMNERA 300M

Channels

General/Advanced Imaging

view channel
Image: Example snapshots of the photon energy density at t = 0.5, 0.7, 0.9, 1.1 nanoseconds (ns) on the y = 2.0 cm plane (Horie, S., Yajima, H., Abe, M. et al., Biomedical Engineering Letters (2026). DOI: 10.1007/s13534-026-00578-9)

AI Tool Enables Real-Time Diffuse Optical Tomography for Brain Lesion Detection

Diffuse optical tomography is a noninvasive imaging technique that uses near-infrared light to detect internal abnormalities such as cerebral hemorrhage and tumors. Its clinical utility for real-time ... Read more

Industry News

view channel
Image: MIM KineticID is 510(k)-pending software for dynamic PET imaging and kinetic modeling, enabling time-based radiotracer analysis for clinical and research decisions (Photo courtesy of GE Healthcare)

GE HealthCare Showcases AI-Enabled Nuclear Medicine Portfolio at SNMMI 2026

Nuclear medicine is expanding rapidly as health systems adopt theranostics and broaden access to radiopharmaceuticals, increasing demand for scalable operations and consistent diagnostic confidence.... Read more
Copyright © 2000-2026 Globetech Media. All rights reserved.