Diabetes Prediction Using Machine Learning Techniques: A Case Study from Jordan
Diabetes is one of the most common diseases in Jordan. It is the main reason of death among Jordanian adult citizens. Worldwide, 48% of all deaths are due to Diabetes occurred before the age of 70 years. Hence, this research is interested in the early prediction of this disease among Jordanian people. To achieve this main objective, Machine Learning (ML) is utilized through a large number of classification models and considering five well-known evaluation metrics. These classification models have been trained on a primary dataset that has been collected for the purpose of the research. The results revealed that BayesNet and NaiveBayes are the best classification models to handle the task of the early prediction of Diabetes in Jordan
Authors
- Maram Y. Al-Safarini
- Ghassan Samara (ORCID: https://orcid.org/0000-0001-8415-0572)
- Ali Elrashidi (ORCID: https://orcid.org/0000-0002-8560-1395)
- Raed Alazaidah (ORCID: https://orcid.org/0000-0002-1818-4288)
- Mo’ath Alluwaici
- Ahmad Abdelhafiz Ali Samhan (ORCID: https://orcid.org/0000-0001-6766-1119)
- Deana Al-omari
- Radwan M. Batyha
- Esraa Al Henawi
Institutions
- Applied Science Private University (JO)
- Zarqa University (JO)
- University of Business and Technology (SA)
Publication Details
- Published
- 2024-12-10
- DOI
- https://doi.org/10.1109/acit62805.2024.10876980
- Primary Topic
- Artificial Intelligence in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 0.00