Models for predicting the quality of life domains on the general population through the orange data mining approach

Bustanul, Arifin and Dyah, Aryani Perwitasari and Zulkarnain, Zulkarnain and M Rifqi, Rokhman (2022) Models for predicting the quality of life domains on the general population through the orange data mining approach. Pharmaciana, 12 (1): 8. pp. 72-82. ISSN 2088-4559

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The incidence of type 2 diabetes mellitus (DM) has been predicted to increase until 2045 in the world. Furthermore, long-term treatment and lifestyle factors affect the quality of life. This study aims to determine the models that can be used to predict the quality-of-life domains in general population by using Artificial Intelligent (AI) devices. This is a cross-sectional design in which the inclusion criteria were individuals of age above 18 years and has never been diagnosed with diabetes mellitus (both type 1 DM and type 2 DM), fasted for at least 8 hours, and are willing to sign an informed consent after having received an explanation. Participants were asked to fill out two questionnaires, namely the Indonesian version of the Finnish Diabetes Risk Score (FINDRISC) and the EuroQoL-5 Dimensions-5 Level (EQ-5D-5L). The AI application uses Orange® machine learning with three models used in predictive analysis, such as Logistic Regression, Neural Network, and SVM. In addition, the model was evaluated using the sensitivity, precision, and accuracy of the AU-ROC parameters. The results showed that the neural network model based on the AUC value, precision, accuracy, and also the ROC analysis, was the best for predicting the utility index of domains in the EQ-5D-5L questionnaire, based on demographic data and the FINDRISC questionnaire.

Item Type: Article
Uncontrolled Keywords: Prediction, Quality of life, Data mining, Artificial intelligence
Subjects: Computers, Control & Information Theory > Computer Software
Computers, Control & Information Theory > Information Theory
Computers, Control & Information Theory > Applications Software
Depositing User: - Diana Permata Sari
Date Deposited: 08 Mar 2023 03:39
Last Modified: 08 Mar 2023 03:39

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