Toward reliable diabetes prediction: Innovations in data engineering and machine learning applications
This excellent research finding indicates that the proposed models might be employed to produce more accurate diabetes predictions to supplement current preventative interventions to reduce the incidence of diabetes and its associated costs.
Authors
- Majdi Khalid
- Md. Alamin Talukder (ORCID: https://orcid.org/0000-0002-3192-1000)
- Md. Manowarul Islam (ORCID: https://orcid.org/0000-0002-3075-9048)
- Mohammad Ali Moni (ORCID: https://orcid.org/0000-0003-0756-1006)
- Mohsin Kazi (ORCID: https://orcid.org/0000-0002-5611-0378)
- Arnisha Akhter (ORCID: https://orcid.org/0000-0001-6342-0916)
- Md. Ashraf Uddin (ORCID: https://orcid.org/0000-0002-4316-4975)
Institutions
- Deakin University (AU)
- The University of Queensland (AU)
- Umm al-Qura University (SA)
- King Saud University (SA)
- Jagannath University (BD)
- International University of Business Agriculture and Technology (BD)
Publication Details
- Journal
- Digital Health
- Published
- 2024-08-21
- DOI
- https://doi.org/10.1177/20552076241271867
- Citations
- 27
- Primary Topic
- Artificial Intelligence in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 19.11
Funders
- King Saud University