A team from Baylor College of Medicine tested automating a version of the large language model across over 332,000 noncontrast…
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From AI breakthroughs to imaging trends, we serve up real-time radiology insights.
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Investigators test ChatGPT-4 Turbo for radiology AI monitoring
Researchers from Baylor College of Medicine and the Radiology Partners Research Institute tested automating a version of the LLM…
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AI boosts rads' identification of incidental PE on CT imaging
Study results suggest that AI could serve as an effective ‘second look’ tool for incidental pulmonary emboli (PE) on CT imaging…
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Is imaging being used to its full potential to diagnose dementia?
As disease-modifying therapies for various types of dementia become more available, MR and CT imaging predominate for diagnosis…
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Open-source DL model does well for identifying lung cancer risk
An open-source, deep-learning (DL) model called Sybil performs well when it comes to predicting lung cancer risk among heavy-smoking…
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CT distinguishes between accidental and abusive head trauma in infants
CT can help clinicians differentiate accidental head trauma from trauma caused by abuse in infants, researchers have reported.
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CT may best conventional measurements for assessing BMD in diabetics
CT may offer a better picture of fracture risk than conventional bone mineral density (BMD) measurements in people with diabetes…
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CT colonography screening program sets benchmarks
Researchers report on 20-year, large institutional CT colonography screening program.
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Thoracic radiologists publish recommendations for post-COVID CT imaging
A group of thoracic radiologists has published a consensus statement on best practices in CT imaging of post-COVID patients.
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Thoracic radiologists publish post-COVID CT imaging recommendations
A group of thoracic radiologists has published a consensus statement on best practices in CT imaging of post-COVID patients.