Predicting malnutrition‐based anemia in geriatric patients using machine learning methods
The study showed that anemia can be predicted with high accuracy in geriatric patients without hemogram data. Additionally, our geriatric data set was shared with researchers for future research. Thus, it has contributed to the literature by opening a new path for studies on subjects such as comparing classification performances with new methodologies or predicting different diseases in geriatric patients.
Authors
- Cemal Aktürk (ORCID: https://orcid.org/0000-0003-3764-3862)
- İbrahim Halil Türkbeyler (ORCID: https://orcid.org/0000-0002-5489-1692)
- Tarık Talan (ORCID: https://orcid.org/0000-0002-5371-4520)
- Mehmet Göl (ORCID: https://orcid.org/0000-0003-4593-3990)
- Mehmet Sait Vural (ORCID: https://orcid.org/0000-0003-2144-5474)
Institutions
- Gaziantep İslam Bilim ve Teknoloji Üniversitesi
- Gaziantep University (TR)
Publication Details
- Journal
- Journal of Evaluation in Clinical Practice
- Published
- 2024-09-23
- DOI
- https://doi.org/10.1111/jep.14142
- Citations
- 6
- Primary Topic
- Artificial Intelligence in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 4.25