A new study shows that deep learning models trained on large sets of cancer genetic and tissue histology data can easily identify the institution that submitted the images.
GE Healthcare Xeleris V virtual processing and review solution eliminates the need for a standalone nuclear medicine workstation so that clinicians can have secure access to data from various locations.
The Rhino Health Platform connects hospitals and AI developers, providing access to a large, continually updated, distributed dataset from a diverse group of patients.
Scientists have used artificial intelligence to improve the accuracy and reliability of an MRI brain-mapping technique, a new study reports.
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Using machine learning, researchers have identified novel, distinct patterns of coordinated activity between different parts of the brain in people with major depressive disorder—even when different protocols are used to detect these brain networks.
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An automated AI measurement of visceral fat area on abdominal CT images predicts future heart attack or stroke risk better than overall weight or BMI.
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Researchers at Massachusetts General Hospital have developed a deep learning model that identifies imaging biomarkers to predict a patient’s risk for developing breast cancer.
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Researchers from multiple institutions in North America have developed a fully automated, deep-learning, artificial-intelligence clinical tool that can measure the volume of cerebral ventricles on MRIs in children within about 25 minutes.
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