DIABETES PREDICTION USING MULTILAYER PERCEPTRON

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dc.contributor.authorTumgoyev, Yussup
dc.date.accessioned2022-06-30T10:44:08Z
dc.date.available2022-06-30T10:44:08Z
dc.date.issued2022-05
dc.description.abstractDiabetes mellitus is one of the most popular diseases that causes 1,5 million people to die each year. It is the major cause of blindness, kidney failure, heart attacks, stroke, and lower limb amputation. Being the world’s top 9 severe diseases, diabetes puts a burden on the world’s economy and the healthcare system. There are two types of diabetes. Type 1 is generic and in the vast majority of cases shows up early in life. This study focuses on type 2 diabetes which is around 90% of all diabetes cases, and that can be diagnosed. Early diagnosis of diabetes can prevent serious medical complications. In this literature, we are introducing a framework of diabetes prediction based on a Multilayer Perceptron of only 1 hidden layer and 8 neurons, which is lighter than the state-of-art framework which consists of 3 hidden layers and 144 neurons in total. The grid-search method was used for hyperparameter tuning to maximize Area Under the ROC Curve (AUC) that was chosen as a performance met- ric. Pima Indian Diabetes Dataset was used to conduct the experiments. The dataset was preprocessed with outlier rejection, missing values imputation, standardization, data scaling, and feature selection algorithms. K-fold cross-validation technique was used to train/test the classification model. The Multilayer Perceptron model was tuned with various hyperparameters as well as the dynamic learning rate. Finally, the best lightweight MLP model consisting of 1 hidden layer that reaches the AUC of 0.90 was obtained. The model performs as well as the state-of-art but is at least 5 times faster in training and more than 80 times more efficient in terms of memory usage.en_US
dc.identifier.citationTumgoyev, Y. (2022). DIABETES PREDICTION USING MULTILAYER PERCEPTRON (Unpublished master's thesis). Nazarbayev University, Nur-Sultan, Kazakhstanen_US
dc.identifier.urihttp://nur.nu.edu.kz/handle/123456789/6358
dc.language.isoenen_US
dc.publisherNazarbayev University School of Engineering and Digital Sciencesen_US
dc.rightsAttribution-NonCommercial-ShareAlike 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/us/*
dc.subjectType of access: Open Accessen_US
dc.subjectResearch Subject Categories::TECHNOLOGYen_US
dc.subjectWorld Health Organizationen_US
dc.subjectWHOen_US
dc.subjectPima Indian Diabetes Dataseten_US
dc.subjectdiabeteen_US
dc.subjectSupport Vector Machineen_US
dc.subjectconvolutional neural networksen_US
dc.subjectCNNen_US
dc.titleDIABETES PREDICTION USING MULTILAYER PERCEPTRONen_US
dc.typeMaster's thesisen_US
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