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  • Deep learning model aids differentiation of colon cancer, acute diverticulitis

    The researchers found that for the test set, the 3-D CNN reached a sensitivity and specificity of 83.3 and 86.6 percent, respectively, compared with the mean reader sensitivity and specificity of 77.6 and 81.6 percent, respectively. There was significant improvement for the combined group of readers with AI support, from a sensitivity of 77.6 to 85.6 percent and from a specificity of 81.6 to 91.3 percent. The number of false-negative and false-positive findings were also reduced with AI support.

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  • Technical adequacy of artificial intelligence body composition assessed in external CT

    The automated AI body composition tools had high technical adequacy rates in a heterogeneous sample of external CT examinations, supporting the tools' generalizability and potential for broad use," concluded head researcher B. Dustin Pooler, MD, from the University of Wisconsin School of Medicine & Public Health in Madison.

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  • Researchers help develop new MRI, expanding access to life-saving imaging

    The Ohio State University Wexner Medical Center is the first in the United States to install this recently FDA-approved full body MRI for patient care. The technology uses a lower magnetic field to open up new possibilities for imaging the lungs and patients with implanted devices and will potentially support new interventional procedures that could result in less radiation exposure.

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  • New MRI technique could pave the way to quicker assessment of multiple sclerosis

    Multiple sclerosis is a disease of the central nervous system that manifests itself in changes (lesions) primarily in the brain. As yet, there is no cure for MS, but it can be effectively treated.

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  • What are PET scans, and what are their uses?

    Positron emission tomography is an imaging technique that uses radiation to show activity within the body on a cellular level. People more commonly refer to it as a PET scan.

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