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ECR: Radiographers optimistic about AI's role in future work

AuntMinnie

While radiographers are concerned about job security, they are also optimistic about AI’s role in their future workflows, according to a presentation given March 1 at ECR 2024. Radiographers appear optimistic about the future of radiographer job roles and responsibilities,” Walsh said. Of the total respondents, 31.3%

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AI functions in x-ray systems may save radiographers time

AuntMinnie

Intelligent virtual and AI-based collimation features appear to save radiographers time during x-ray image acquisitions – a key function for enabling more patient-focused workflows, according to a recent study. ATC and SVO enable the radiographer to save time during chest or stitched examinations. The full study is available here.

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Julianna Czum talks AI chest radiograph study with AuntMinnie.com

AuntMinnie

million chest radiographs. The team reported that the algorithm could successfully triage pairs of chest radiographs showing no change while detecting urgent interval changes during longitudinal follow-up. Julianna Czum, MD, from Johns Hopkins University wrote an editorial accompanying the study.

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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). Hwang et al.

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Can We Upskill Radiographers through Artificial Intelligence? 

The British Institute of Radiology

Shamie Kumar describes how AI fits into a radiology clinical workflow and her perspective on how a clinical radiographer could use this to learn from and enhance their skills. If the AI findings are seen in PACS, how many radiographers actually log into PACS after taking a scan or X-ray? Can Radiographers Up-Skill?

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Injury Prediction Rule Reduces Radiographic Imaging Exposure in Children

MedImaging Radiography

A highly accurate prediction rule for cervical spine injuries in children reduces the use of CT scans by over 50% without missing clinically significant injuries or increasing the use of unnecessary X-rays.

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Radiographers struggle with communication, care for suicidal patients

AuntMinnie

Radiographers have difficulty communicating with and caring for patients wh. Read more on AuntMinnie.com Related Reading: Radiologists seeing declines in reimbursement per beneficiary Was burnout really worse for radiologists during the pandemic? Could phone tree system help with radiologist burnout? Trying to stop burnout?