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dc.contributor.advisorMcGregor, Carolyn
dc.contributor.authorYeung, Jennifer
dc.date.accessioned2022-04-19T14:42:22Z
dc.date.accessioned2022-06-13T15:27:21Z
dc.date.available2022-04-19T14:42:22Z
dc.date.available2022-06-13T15:27:21Z
dc.date.issued2022-03-01
dc.identifier.urihttps://hdl.handle.net/10155/1435
dc.description.abstractComputing frameworks that utilize big data analytics to support Clinical Decision Support Systems (CDSS) have proven to impact human lives in applications on Earth and in space. In the application of Space Medicine Decision Support Systems (SMDSS) on ISS missions and future space missions to the Moon and Mars, there is no known methodology that supports the unique challenges of human physiology in microgravity where countermeasure activities are conducted to help astronaut adaptation to spaceflight. There exist challenges in data integration, data synchronization, and spacecraft-to-ground communication limitations. To help address these challenges, this thesis proposes a framework for SMDSS that extends an existing big data online health analytics platform, Artemis, to support Clinical and Countermeasure Decision Support Systems. This framework has been instantiated by extending the Artemis platform. This is demonstrated within the context of countermeasure activities on the International Space Station (ISS) and a firefighter cold stress training activity.en
dc.description.sponsorshipUniversity of Ontario Institute of Technologyen
dc.language.isoenen
dc.subjectSpace medicine decision support systemen
dc.subjectInformation systemsen
dc.subjectCloud computingen
dc.subjectBig data analyticsen
dc.subjectOnline health analyticsen
dc.titleA big data and online health analytics framework extended to integrate clinical and countermeasure decision supporten
dc.typeThesisen
dc.degree.levelMaster of Science (MSc)en
dc.degree.disciplineComputer Scienceen


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