Prediction of Myopia Among Undergraduate Students Using Ensemble Machine Learning Techniques
These findings demonstrate the effectiveness of ensemble machine learning in predicting myopia and highlight the potential for early intervention strategies. By identifying high-risk individuals, targeted awareness programs and lifestyle modifications can help mitigate myopia progression among undergraduate students.
Authors
- Md. Parvez Mosharaf
- Jean‐Sébastien Roy (ORCID: https://orcid.org/0000-0003-2853-9940)
- Farhana Hasan
- Md. Kaderi Kibria (ORCID: https://orcid.org/0000-0002-3189-7012)
- Isteaq Kabir Sifat (ORCID: https://orcid.org/0009-0003-3724-1166)
- Nourin Sultana (ORCID: https://orcid.org/0009-0004-4205-1815)
- Tajin Ahmed Jisa (ORCID: https://orcid.org/0009-0006-0901-8743)
Institutions
- University of Southern Queensland (AU)
- Hajee Mohammad Danesh Science and Technology University (BD)
- University of Rajshahi (BD)
Publication Details
- Journal
- Health Science Reports
- Published
- 2025-05-01
- DOI
- https://doi.org/10.1002/hsr2.70874
- Citations
- 2
- Primary Topic
- Ophthalmology and Visual Impairment Studies
- Type
- article
- Field-Weighted Citation Impact
- 2.71