Decision tree-based learning and laboratory data mining: an efficient approach to amebiasis testing
The application of ML to EMR can accurately predict amebiasis. This finding significantly contributes to the emerging use of ML as a decision support system in parasitic disease diagnosis.
Authors
- Ahmad B. Hassanat (ORCID: https://orcid.org/0000-0002-9991-304X)
- Enas Al-khlifeh
- Malek Alrashidi (ORCID: https://orcid.org/0000-0001-8460-9240)
- Khalid Almohammadi (ORCID: https://orcid.org/0000-0003-0813-142X)
- Ahmad S. Tarawneh
- Ramadan Hassanat
Institutions
- Mutah University (JO)
- King Hussein Medical Center (JO)
- Al-Balqa Applied University (JO)
- University of Tabuk (SA)
Publication Details
- Journal
- Parasites & Vectors
- Published
- 2025-01-29
- DOI
- https://doi.org/10.1186/s13071-024-06618-6
- Citations
- 3
- Primary Topic
- Amoebic Infections and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 4.19