Predicting Mortality of Diabetic ICU Patients

dc.contributor.advisorLiu, Xinlian
dc.contributor.advisorDong, Aijuan
dc.contributor.authorWittler, Ian
dc.contributor.departmentComputer Scienceen_US
dc.contributor.programHood College Departmental Honors
dc.date.accessioned2019-04-29T19:33:23Z
dc.date.available2019-04-29T19:33:23Z
dc.date.issued2019-04
dc.description.abstractDiabetes mellitus (DM) is a major public health concern that requires continuing medical care. It is also a leading cause of other serious health complications associated with longer hospital stays and increased mortality rates. Fluctuation of blood glucose levels are easy to monitor. Physicians manage patients' blood glucose to prevent or slow the progress of diabetes. In this paper, the MIMIC-III data set is used to develop and train multiple models that aim to predict the mortality of DM patients. Our deep learning model of convolutional neural network produced a 0.885 AUC score, above all baseline models we constructed, which include decision trees, random forests, and fully connected neural networks. The inputs for each model were comprised of admission type, age, Elixhauser comorbidity score, blood glucose measurements, and blood glucose range. The results obtained from these models are valuable for physicians, patients, and insurance companies. By analyzing the features that drive these models, care management for diabetic patients in an ICU setting can be improved resulting in lowered motality rate.en_US
dc.format.extent9 pagesen_US
dc.identifierdoi:10.13016/m2dqpi-xbnk
dc.identifier.urihttp://hdl.handle.net/11603/13527
dc.language.isoen_USen_US
dc.relation.isAvailableAtHood College
dc.rightsAttribution 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/us/*
dc.subjectdata miningen_US
dc.subjectdiabetes mellitusen_US
dc.subjectconvolutional neural networksen_US
dc.titlePredicting Mortality of Diabetic ICU Patientsen_US
dc.typePaperen_US

Files

Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
WittlerHonors.pdf
Size:
563.63 KB
Format:
Adobe Portable Document Format
Description:
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
2.01 KB
Format:
Item-specific license agreed upon to submission
Description: