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Researchers at the University of Arizona’s Center for Innovation in Brain Science will apply a big-data approach to enable researchers to better understand the systems biology of the disease and other neurodegenerative diseases.January 8
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Using machine learning, researchers at Beth Israel Deaconess Medical Center have developed a less-invasive alternative to liver biopsy—considered the gold standard for the diagnosis of non-alcoholic fatty liver disease.December 4
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Using electrocardiogram data, Geisinger researchers have trained deep neural networks to predict patients’ risk of developing a potentially dangerous irregular heartbeat or of dying within the next 12 months.November 11
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Researchers have identified the 10 top predictors of future heart failure for patients living with type 2 diabetes by using a machine learning model that generates a risk score.September 16
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Geisinger has teamed with Big Blue to better diagnose and treat patients with sepsis, a potentially life-threatening condition, using machine learning.September 12
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Researchers from Children’s National Health System are looking to see if predictive modeling can be used to anticipate rare diseases.July 15
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Researchers from Children’s National Health System are looking to see if predictive modeling can be used to anticipate rare diseases.July 15
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Researchers at the Stanford University School of Medicine have developed a computer algorithm that provides more accurate prognoses for cancer patients by integrating different types of predictive data.July 10
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The ability to predict future case volume in operating rooms is critical to ensuring that a hospital’s staffing levels are properly matched to the projected workload to achieve maximum efficiency.May 6
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Imaging biomarkers, when teamed with magnetic resonance imaging, has the potential to reduce the need for liver biopsies.November 9
