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dc.contributor.authorOlszewski, Daniel
dc.date.accessioned2020-04-30T10:46:54Z
dc.date.available2020-04-30T10:46:54Z
dc.date.issued2019-04-25
dc.identifier.urihttps://scholars.carroll.edu/handle/20.500.12647/7307
dc.description.abstractWith the dawn of deep learning, the applications are numerous. Biomedical data lacks the abundance of readily available data. In order to apply these new deep learning algorithms, we need to use novel methods to be able to do so. This presentation will go over some of these methods, and their application to improving radiation therapy.
dc.titleDeep Learning on Small Data: Guiding Radiation Therapy with Neural Networks
carrollscholars.object.disciplinesApplied Mathematics; Applied Statistics; Biostatistics
carrollscholars.legacy.itemurlhttps://scholars.carroll.edu/surf/2019/all/2
carrollscholars.legacy.contextkey14360833
carrollscholars.object.majorMathematics, Computer Science and Data Science
carrollscholars.object.fieldofstudyApplied Data Science in Biology
carrollscholars.location.campusbuildingCampus Center - Siena
carrollscholars.event.startdate4/25/2019 13:15
carrollscholars.event.enddate4/25/2019 13:30
carrollscholars.contributor.institutionCarroll College


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