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Deep-Learning Chest Radiograph Model Predicts Mortality for Community-Acquired Pneumonia

Imaging Technology

In this AJR accepted manuscript , a DL model was developed in 7,105 patients via one institution from March 2013 to December 2019 (3:1:1 allocation to training, validation, and internal test sets) to predict risk of all-cause mortality within 30 days after CAP diagnosis using patients’ initial chest radiograph. CURB-65 score). “The

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Can AI help chest DDR achieve clinical adoption?

AuntMinnie

Chest dynamic digital radiography (DDR) may have received a boost toward clinical use in patients with lung disorders, with researchers developing AI to perform time-consuming analysis involved in the technology, according to researchers in New York City. a) Raw example of a dynamic digital radiograph. (b)

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CMCU Digital Radiography (DR) Group Introduces Clinical White Paper on Intelligent Noise Reduction in Pediatric Radiography Study

Imaging Technology

The company will showcase the clinical analysis of Canon’s Intelligent Noise Reduction (Intelligent NR) that provides superior image quality while lowering radiation dosing in pediatric digital radiography at the Radiological Society of North America Annual Meeting 2023 (RSNA) , McCormick Place Convention Center, Chicago, IL Nov.

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Can AI help rule out ‘unremarkable’ chest x-rays?

AuntMinnie

The finding by researchers in Copenhagen, Denmark, suggests that AI could eventually help streamline high-volume radiology workflows by handling some of the more “tedious parts of the work,” lead author Louis Plesner, MD, of Herlev and Gentofte Hospital in Denmark told AuntMinnie.com. The full study can be found here.

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Meet the Minnies 2024 finalists

AuntMinnie

Most Influential Radiology Researcher Erik Middlebrooks, MD, Mayo Clinic, Jacksonville, FL Erik Middlebrooks, MD. One of this year's nominations for Most Influential Radiology Researcher is Erik Middlebrooks, MD, of the Mayo Clinic in Jacksonville, FL. He earned his medical degree from Washington University in St.

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AI improves x-ray reads for rads with varying experience

AuntMinnie

Gleamer) increased sensitivity for detecting all abnormalities on x-rays for all readers (thoracic radiologists, general radiologists, and radiology residents), according to a group of Gleamer consultants and clinicians at Cochin Hospital in Paris. In a retrospective study, a commercially available algorithm (ChestView, v.

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Deep learning combines breast imaging data to predict cancer prognosis

AuntMinnie

Deep-learning models could have potential as predictive tools for breast cancer prognosis, a study published January 17 in Clinical Breast Cancer has found. From there, the team used clinical data and imaging characteristics to select independent prognostic factors to establish a clinical model.