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APPLYING OPERATIONS RESEARCH MODELS TO PROBLEMS IN HEALTH CARE

dc.contributor.advisorGolden, Bruceen_US
dc.contributor.authorPrice, Stuart Patricken_US
dc.date.accessioned2015-06-25T05:57:47Z
dc.date.available2015-06-25T05:57:47Z
dc.date.issued2015en_US
dc.identifierhttps://doi.org/10.13016/M2132R
dc.identifier.urihttp://hdl.handle.net/1903/16565
dc.description.abstractIntensity- modulated radiation therapy is a form of cancer treatment that directs high energy x-rays to irradiate a tumor volume. In order to minimize the damage to surround-ing tissue the radiation is delivered from multiple angles. The selection of angles is an NP-hard problem and is currently done manually in most hospitals. We use previously evaluated treatment plans to train a machine learning model to sort potential treatment plans. By sorting potential treatment plans we can find better solutions while only evalu-ating a fifth as many plans. We then construct a genetic algorithm and use our machine learning models to search the space of all potential treatment plans to suggest a potential best plan. Using the genetic algorithm we are able to find plans 2% better on average than the previously best known plans. Proton therapy is a new form of radiation therapy. We simulated a proton therapy treatment center in order to optimize patient throughput and minimize patient wait time. We are able to schedule patients reducing wait times between 20% and 35% depending on patient tardiness and absenteeism. Finally, we analyzed the impact of operations research on the treatment of pros-tate cancer. We reviewed the work that has been published in both operations research and medical journals, seeing how it has impacted policy and doctor recommendations.en_US
dc.language.isoenen_US
dc.titleAPPLYING OPERATIONS RESEARCH MODELS TO PROBLEMS IN HEALTH CAREen_US
dc.typeDissertationen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.contributor.departmentBusiness and Management: Decision & Information Technologiesen_US
dc.subject.pqcontrolledOperations researchen_US
dc.subject.pqcontrolledMedical imaging and radiologyen_US
dc.subject.pquncontrolledIMRTen_US
dc.subject.pquncontrolledMachine Learningen_US
dc.subject.pquncontrolledSchedulingen_US


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