Agenda setting for health equity assessment through the lenses of social determinants of health using machine learning approach: a framework and preliminary pilot study
The findings underscore the significance of employing innovative methods like CRISP-ML(Q) and ML algorithms to enhance health equity. Integrating this platform into health systems can help countries better prioritize and address health inequities. The pilot implementation demonstrated these methods' practical applicability and effectiveness, aiding policymakers in making informed decisions to improve health equity.
Authors
- Hakimeh Mostafavi
- Ali Akbar Fazaeli (ORCID: https://orcid.org/0000-0002-6667-0344)
- Ahad Bakhtiari (ORCID: https://orcid.org/0000-0003-3580-9259)
- Alireza Olyaeemanesh (ORCID: https://orcid.org/0000-0002-7417-2417)
- Mohammadreza Mobinizadeh (ORCID: https://orcid.org/0000-0003-3691-3744)
- Hamid Reza Rabiee (ORCID: https://orcid.org/0000-0002-9835-4493)
- Amirhossein Takian (ORCID: https://orcid.org/0000-0001-7806-5558)
- Saharnaz Sazgarnejad
- Efat Mohamadi (ORCID: https://orcid.org/0000-0003-2297-7990)
- Maryam Ramezani (ORCID: https://orcid.org/0000-0001-5044-2526)
- Alireza Atashi (ORCID: https://orcid.org/0000-0002-9923-9665)
Institutions
- Sharif University of Technology (IR)
- University of Tehran (IR)
- Tehran University of Medical Sciences (IR)
Publication Details
- Journal
- BioData Mining
- Published
- 2025-02-10
- DOI
- https://doi.org/10.1186/s13040-025-00428-x
- Citations
- 1
- Primary Topic
- Health disparities and outcomes
- Type
- article
- Field-Weighted Citation Impact
- 2.17
Funders
- Tehran University of Medical Sciences and Health Services