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
Sign In
Advertise with Us

Download Mobile App

AI Tool Accurately Detects Normal and Abnormal Chest X-Rays

By MedImaging International staff writers
Posted on 09 Mar 2023
Print article
Image: An AI tool can accurately identify normal and abnormal chest X-rays in a clinical setting (Photo courtesy of Pexels)
Image: An AI tool can accurately identify normal and abnormal chest X-rays in a clinical setting (Photo courtesy of Pexels)

Chest X-rays are an essential diagnostic tool for identifying various conditions related to the heart and lungs, including cancer and chronic lung diseases. However, the interpretation of chest X-rays is a time-consuming and burdensome task for radiologists worldwide. Now, a new study has found that an artificial intelligence (AI) tool can accurately identify normal and abnormal chest X-rays in a clinical setting. The AI tool could greatly reduce the workload of radiologists and improve the efficiency of diagnosing and treating patients.

In the retrospective, multi-center study, researchers at Herlev and Gentofte Hospital (Copenhagen, Denmark) assessed the reliability of using an AI tool that was capable of identifying normal and abnormal chest X-rays. Using a commercially available AI tool, the researchers analyzed the chest X-rays of 1,529 patients from four hospitals in Denmark. The study included chest X-rays from emergency department patients, in-hospital patients and outpatients. The AI tool classified the X-rays as either “high-confidence normal” or “not high-confidence normal” as in normal and abnormal, respectively. The study employed two board-certified thoracic (chest) radiologists as the reference standard, and used a third radiologist in cases of disagreements, with all the three physicians remaining blinded to the AI results.

Out of the 429 chest X-rays classified as normal, the AI tool also classified 120, or 28%, as normal. This suggests that the AI tool could potentially safely automate these X-rays, or 7.8 % of all the X-rays. The AI tool also identified abnormal chest X-rays with 99.1% sensitivity. The researchers expect to conduct further studies toward a larger prospective implementation of the AI tool where the autonomously reported chest X-rays are still reviewed by radiologists. The AI tool did particularly well in identifying normal X-rays of the outpatient group at a rate of 11.6%, indicating that it can perform especially well in outpatient settings with a high prevalence of normal chest X-rays.

“The most surprising finding was just how sensitive this AI tool was for all kinds of chest disease,” said study co-author Louis Lind Plesner, M.D., from the Department of Radiology at the Herlev and Gentofte Hospital. “In fact, we could not find a single chest X-ray in our database where the algorithm made a major mistake. Furthermore, the AI tool had a sensitivity overall better than the clinical board-certified radiologists.”

Related Links:
Herlev and Gentofte Hospital

Gold Supplier
Conductive Gel
Gold Supplier
IMRT Thorax Phantom
CIRS Model 002LFC
Point-Of-Care Ultrasound (POCUS) System
Sonosite ST
Silver Supplier
Bucky Protector
Bucky Protector

Print article
Sun Nuclear -    Mirion



view channel
Image: The new device targets ultrasound waves to precise spots in the brain (Photo courtesy of WUSTL)

Anatomically Precise Ultrasound-Based Technique to Enable Noninvasive Biopsies for Brain Tumors

The blood-brain barrier serves as a protective wall, keeping the brain safe from harmful elements like viruses and toxins in the blood. This makes it challenging for doctors to obtain molecular and genetic... Read more

Nuclear Medicine

view channel
Image: Imaging entire body instead of only the primary cancer site can provide a total estimate of HER2 expression (Photo courtesy of 123RF)

Whole-Body PET/CT Predicts Response to HER2-Targeted Therapy in Metastatic Breast Cancer Patients

Around 20% of women diagnosed with breast cancer show overexpression of human epidermal growth factor receptor 2 (HER2), making it a key therapy target for new as well as recurring cases.... Read more

General/Advanced Imaging

view channel
Image: Annalise Enterprise CTB acts like a ‘second pair of eyes’ for radiologists (Photo courtesy of Annalise.ai)

Deep Learning System Boosts Radiologist Accuracy and Speed for Head CTs

Non-contrast computed tomography of the brain (NCCTB) is a commonly employed method for identifying intracranial pathology. Despite its frequent use, the complex scan outcomes are prone to being misunderstood.... Read more

Imaging IT

view channel
Image: The new Medical Imaging Suite makes healthcare imaging data more accessible, interoperable and useful (Photo courtesy of Google Cloud)

New Google Cloud Medical Imaging Suite Makes Imaging Healthcare Data More Accessible

Medical imaging is a critical tool used to diagnose patients, and there are billions of medical images scanned globally each year. Imaging data accounts for about 90% of all healthcare data1 and, until... Read more

Industry News

view channel
Image: The partnership combines best-in-class AI-powered technologies for musculoskeletal imaging workflows (Photo courtesy of ImageBiopsy Lab)

AI-Powered Technologies to Aid Interpretation of X-Ray and MRI Images for Improved Disease Diagnosis

Musculoskeletal (MSK) conditions impact more people worldwide than issues related to the circulatory or respiratory systems. Even so, diagnostic procedures for these conditions often still lean on outdated... Read more
Copyright © 2000-2023 Globetech Media. All rights reserved.