Key result
Machine learning helps analyze complex social determinants of health to design health equity interventions.
Why the study?
To connect population and public health research with machine learning work, activate the machine learning community on these topics, and highlight opportunities to achieve health equity.
Highlights opportunities for synergy between machine learning and population/public health to achieve health equity.
Answers are grounded in this paper and cite their sources.
May guide equity-focused strategies using machine learning; leaves open the need for prospective validation before clinical adoption.
Research in population and public health focuses on the mechanisms between different cultural, social, and environmental factors and their effect on the health, of not just individuals, but communities as a whole. We present here a very brief introduction into research in these fields, as well as connections to existing machine learning work to help activate the machine learning community on such topics and highlight specific opportunities where machine learning, public and population health may synergize to better achieve health equity.
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Mhasawade et al. (2020) conducted a review in Population and Public Health. Machine Learning was evaluated. Machine learning techniques provide opportunities to analyze complex multi-level social determinants of health and design interventions to achieve health equity.
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