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Radiography

Image: A new X-ray imaging method could decisively improve breast cancer diagnostics (Photo courtesy of Freepik)

3D X-Ray Imaging Technique to Significantly Improve Breast Cancer Detection

Researchers have successfully enhanced mammography, an X-ray imaging technique used for early-stage tumor detection, leading to significantly improved reliability and a less distressing experience for suspected breast cancer patients. More...
20 Jul 2023
Image: An artificial intelligence-based model classifies cardiac functions from chest radiographs (Photo courtesy of Osaka Metropolitan University)

Groundbreaking AI-Based Method Accurately Classifies Cardiac Function and Disease Using Chest X-Rays

An innovative artificial intelligence tool uses chest X-rays to classify cardiac functions and identify valvular heart disease with unprecedented accuracy. More...
07 Jul 2023
Image: The Lunit INSIGHT CXR chest X-ray AI analysis solution (Photo courtesy of Lunit)

High-Accuracy AI Model Can Improve Radiologists' Chest X-Ray Analysis Performance

A recent study presents compelling evidence that a high-accuracy AI model can significantly enhance radiologists' ability to analyze chest X-rays. More...
04 Jul 2023
BoneView integrates seamlessly with all IT infrastructures (Photo courtesy of GLEAMER)

AI-Powered Fracture Detection Solution Reduces Risk of Misdiagnosis

An AI-enabled fracture detection solution offers an instant and automatic second read of trauma X-rays, fully integrated into the reading workflow. More...
03 Jul 2023
Image: A high accuracy AI algorithm improves lung cancer detection (Photo courtesy of Seoul National University)

High Accuracy AI Improves Radiologist Performance in Detecting Lung Cancers on Chest X-Rays

A study has found that an AI algorithm with high diagnostic accuracy can enhance radiologist performance in identifying lung cancers on chest X-rays and increase human acceptance of AI recommendations. More...
28 Jun 2023
Image: Deep learning could better guide clinical decision-making in patients with pneumonia (Photo courtesy of Freepik)

Deep Learning Model Accurately Predicts Pneumonia Mortality on Chest X-Rays

A deep learning-based model that utilizes initial chest X-rays has shown potential in accurately predicting 30-day mortality, outperforming the well-established risk prediction tool, the CURB-65 score. More...
23 Jun 2023
Image: Ultrasound can be used instead of X-rays to detect arm fractures in children (Photo courtesy of Freepik)

Ultrasound as Good as X-Ray at Diagnosing Arm Fractures in Children

A research team exploring the potential use of standard ultrasound machines as an alternative to X-ray machines for diagnosing distal forearm fractures in children has found that ultrasound equipment can be a reliable diagnostic tool. More...
06 Jun 2023
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The MedImaging Radiology channel covers fluoroscopy, digital radiography, computerized tomography, mammography, interventional radiology, and other medical uses of X-ray imaging as well as related instrumentation, trends and safety issues.
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/home/www/medsites/medicalimaging/index.php:409122 queries executed
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103 (30.994415283203): SELECT dp.id, dp.name, dp.title, dp.video, dp.video_source, dp.created FROM jos_deeppockets AS dp WHERE dp.id = 294803276 LIMIT 1
104 (30.040740966797): SELECT dp.id, dp.name, dp.title, dp.video, dp.video_source, dp.created FROM jos_deeppockets_archive AS dp WHERE dp.id = 294803276 LIMIT 1
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108 (337.83912658691): SELECT name FROM jos_deeppockets WHERE id=211
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111 (617.98095703125): SELECT *, DATE_FORMAT(publish_up,'%d %b %Y') AS date_publish_up, DATE_FORMAT(publish_down,'%d %b %Y') AS date_publish_down FROM jos_events WHERE state=1 AND publish_up > NOW() and extra_info REGEXP '((;)|(^))211((;)|($))' AND catid IN (0,110) ORDER BY publish_up ASC LIMIT 3
112 (!!!!! 9021.0437774658): TRUNCATE TABLE jos_trademed_module
113 (!!!!! 1492.977142334): SELECT jos_item.* FROM jos_item INNER JOIN jos_number ON jos_item.numberID=jos_number.id WHERE 1=1 AND (jos_item.imgMini<>'') AND jos_item.type='L' AND jos_item.numberID= ( SELECT jos_number.id FROM jos_number WHERE jos_number.journalID IN (10) and jos_number.id in (select distinct jos_number.id from jos_number join jos_item on jos_item.numberid=jos_number.id where jos_item.type='P') ORDER BY (CONVERT(SUBSTRING(issue,1,2),SIGNED) + (CONVERT(SUBSTRING(issue,3,2),SIGNED)*100)) DESC LIMIT 0,1 ) ORDER BY RAND() DESC LIMIT 6
114 (621.08039855957): select distinct links.* from jos_textlinks links join jos_textlinks_placement placement on links.id=placement.link_id where journal_id=(10) and (channel_id=211 or channel_id is null)
115 (57.93571472168): select distinct links.* from jos_textlinks links join jos_textlinks_placement placement on links.id=placement.link_id where journal_id=(10) and (channel_id=211 or channel_id is null)
116 (68.902969360352): SELECT livesite FROM jos_dp_categories WHERE id=10 AND published='1' LIMIT 1
117 (64.849853515625): select jos_twitters.link from jos_twitters where cat=10
118 (95.844268798828): select jos_facebook.link from jos_facebook where cat=10
119 (54.121017456055): select jos_google_plus.link from jos_google_plus where cat=10
120 (47.922134399414): select jos_linkedin.link from jos_linkedin where cat=10
121 (375.98609924316): update jos_bannersmanager_banner set impmade=impmade+1 where id in(14202,14203)
122 (!!!!! 1867.0558929443): insert into jos_banners_delta values (14202,'2025-08-02 19:10:22','216.73.216.210','view'),(14203,'2025-08-02 19:10:22','216.73.216.210','view')