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                    <title>MRI images reconstructed by artificial intelligence could accelerate and better guide radiotherapy</title>
                    <description>An artificial intelligence (AI) that reconstructs MRI images of moving tumors can do so in seconds, offering a significant improvement on current methods to optimize radiotherapy treatment in the clinic.</description>
                    <link>https://medicalxpress.com/news/2021-06-mri-images-reconstructed-artificial-intelligence.html</link>
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                    <pubDate>Fri, 25 Jun 2021 10:24:47 EDT</pubDate>
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                    <title>World-first in showing clinical-quality Proton CT for treatment of cancer</title>
                    <description>An international team of researchers will for the first time be able to demonstrate clinical-quality proton CT to improve proton therapy in the treatment of cancer – moving a step closer to this improved treatment method being used to help those suffering with certain forms of cancer, particularly for children and young people.</description>
                    <link>https://medicalxpress.com/news/2015-07-world-first-clinical-quality-proton-ct-treatment.html</link>
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                    <pubDate>Tue, 07 Jul 2015 09:32:23 EDT</pubDate>
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                    <title>New computational model can predict breast cancer survival</title>
                    <description>Columbia Engineering researchers, led by Dimitris Anastassiou, Charles Batchelor Professor in Electrical Engineering and member of the Columbia Initiative in Systems Biology, have developed a new computational model that is highly predictive of breast cancer survival. The team, who won the Sage Bionetworks / DREAM Breast Cancer Prognosis Challenge for this work, published their results—&quot;Development of a Prognostic Model for Breast Cancer Survival in an Open Challenge Environment&quot;—in the April 17 issue of Science Translational Medicine.</description>
                    <link>https://medicalxpress.com/news/2013-04-breast-cancer-survival.html</link>
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                    <pubDate>Wed, 17 Apr 2013 14:00:09 EDT</pubDate>
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