Explore more about: Machine Learning

February 24, 2021
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The Medical Imaging and Data Resource Center (MIDRC), a collaboration of leading medical imaging organizations funded by NIBIB, has launched a repository of imaging data to facilitate medical imaging research on COVID-19.
January 19, 2021
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Compared to standard machine learning models, deep learning models are largely superior at discerning patterns and discriminative features in brain imaging, despite being more complex in their architecture.
August 26, 2020
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A new article looks at the use of virtual imaging trials in effective assessment and optimization of CT and radiography acquisitions and analysis tools to help manage the coronavirus disease (COVID-19) pandemic.
August 22, 2020
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NIBIB-funded researchers at NYU Langone Health worked with Facebook AI researchers to develop a method to speed up MRI scans.
August 22, 2020
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NIBIB-funded researchers have developed a way to use artificial intelligence to speed up MRI imaging without sacrificing quality.
August 10, 2020
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The National Institutes of Health has launched an ambitious effort to use artificial intelligence, computation, and medical imaging to enable early disease detection, inform successful treatment strategies, and predict individual disease outcomes of COVID-19.
August 3, 2020
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NIBIB-funded researchers at Stanford University have created an artificial neural network that analyzes lung CT scans to provide information about lung cancer severity that can guide treatment options.
June 29, 2021
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Bioengineers have created a blood-drawing robot that performed as well or better than technicians. The device could increase blood draw success from difficult- to-find veins and allow healthcare workers more time to treat patients.
April 14, 2020
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Bioengineers have combined standard microscopy, infrared light, and artificial intelligence to assemble digital biopsies that identify important molecular characteristics of cancer biopsy samples.
March 15, 2021
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A new deep learning technique constructs better macroscopic medical images of cells and tissues at ultra-fast speeds.