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Ensemble Predictive Modeling for Dementia Diagnosis

  • Near East University
  • Manipal Academy of Higher Education

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The goal of this study is to evaluate and compare the prediction performance of three different models, Multiple Linear Regression (MLR), Artificial Neural Network (ANN), and Adaptive Neuro-Fuzzy Inference System (ANFIS), in predicting dementia. The models were trained and tested using a dataset of 149 participants and nine input variables, with a 70%/30% data split. Performance indicators for evaluation were R2 RMSE, and MSE. The results show that all models correctly predicted dementia, with ANN and ANFIS marginally exceeding MLR in terms of prediction accuracy. The training and testing phases yielded a perfect R2 score of 1, suggesting a strong fit to the dataset. This study contributes to dementia prediction research by providing a detailed review of various models.

Original languageEnglish
Title of host publication17th International Conference on Developments in eSystems Engineering, DeSE 2024
EditorsDhiya Al-Jumeily, Sulaf Assi, Manoj Jayabalan, Jade Hind, Abir Hussain, Hissam Tawfik, Neil Rowe, Jamila Mustafina
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages352-357
Number of pages6
ISBN (Electronic)9798350368697
DOIs
StatePublished - 2024
Event17th International Conference on Developments in eSystems Engineering, DeSE 2024 - Khorfakkan, United Arab Emirates
Duration: 6 Nov 20248 Nov 2024

Publication series

NameProceedings - International Conference on Developments in eSystems Engineering, DeSE
ISSN (Print)2161-1343

Conference

Conference17th International Conference on Developments in eSystems Engineering, DeSE 2024
Country/TerritoryUnited Arab Emirates
CityKhorfakkan
Period6/11/248/11/24

Keywords

  • Adaptive neuro-fuzzy inference systems (ANFIS)
  • Artificial neural network (ANN)
  • Dementia
  • Multiple linear regression (MLR)
  • Prediction

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