ArticleSSM - population health2021
A scoping review on the use of machine learning in research on social determinants of health: Trends and research prospects.
Article in SSM - population health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers, 1 of them a synthesis that pooled it.
What it found
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
42 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Using machine learning methods to predict all-cause somatic hospitalizations in adults: A systematic review.PloS one · 2024Pooled it
- Exploring the Association Between Social Determinants of Health and Telehealth Utilization for Attention-Deficit/Hyperactivity Disorder Among Adults Using Machine Learning: A Cross-Sectional Study.Healthcare (Basel, Switzerland) · 2026Article
- Social cohesion, social capital and mental health: current evidence and future research directions.World psychiatry : official journal of the World Psychiatric Association (WPA) · 2026Article
- Decoding health disparities by gender, ethnicity and chronic diseases across three Latin American countries.Nature communications · 2026Article
- Machine Learning-Based Prediction of Institutional Delivery Dropout (IDD) Among Nigerian Women: An Exploratory Study Using SHAP Interpretability.Journal of epidemiology and global health · 2026Article
- Machine learning-based prediction of fever among under-five children in Ethiopia: A national-level study.PloS one · 2026Article
- Risk prediction models for cardiac rupture after acute myocardial infarction: a systematic review and meta-analysis.Frontiers in cardiovascular medicine · 2026Review
- Identifying determinants of unmet healthcare needs in South Korea: a comparison of machine learning approaches for precision public health.BMC public health · 2025Article
- Multidimensional predictors of preterm birth risk among black and white primiparous women in the U.S.: insights from machine learning.BMC pregnancy and childbirth · 2025Article
- Effective Non-IID Degree Estimation for Robust Federated Learning in Healthcare Datasets.Journal of healthcare informatics research · 2025Article
- A machine learning approach to predict self-efficacy in breast cancer survivors.BMC medical informatics and decision making · 2025Article
- Using machine-learning to identify differences in the association between blood-based biomarkers and later life health across race and ethnicity.The journals of gerontology. Series A, Biological sciences and medical sciences · 2025Article
- Interpretive prediction of hyperuricemia and gout patients via machine learning analysis of human gut microbiome.BMC microbiology · 2025Article
- Contribution of Structure Learning Algorithms in Social Epidemiology: Application to Real-World Data.International journal of environmental research and public health · 2025Article
- Predicting Health-Related Quality of Life Using Social Determinants of Health: A Machine Learning Approach with the All of Us Cohort.Bioengineering (Basel, Switzerland) · 2025Article
- Comparing AI/ML approaches and classical regression for predictive modeling using large population health databases: Applications to COVID-19 case prediction.Global epidemiology · 2024Article
- Diagnostic potential of salivary microbiota in persistent pulmonary nodules: identifying biomarkers and functional pathways using 16S rRNA sequencing and machine learning.Journal of translational medicine · 2024Article
- Machine learning in causal inference for epidemiology.European journal of epidemiology · 2024Article
- Social Determinants of Health and the Use of Community-Based Rehabilitation Following Stroke: Methodologic Considerations.Archives of rehabilitation research and clinical translation · 2024Article
- The Sociodemographic Biases in Machine Learning Algorithms: A Biomedical Informatics Perspective.Life (Basel, Switzerland) · 2024Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMachine learning (ML) has spread rapidly from computer science to several disciplines. Given the predictive capacity of ML, it offers new opportunities for health, behavioral, and social scientists. However, it remains unclear how and to what extent ML is being used in studies of social determinants of health (SDH).
methodsUsing four search engines, we conducted a scoping review of studies that used ML to study SDH (published before May 1, 2020). Two independent reviewers analyzed the relevant studies. For each study, we identified the research questions, Results, data, and algorithms. We synthesized our findings in a narrative report.
resultsOf the initial 8097 hits, we identified 82 relevant studies. The number of publications has risen during the past decade. More than half of the studies (n = 46) used US data. About 80% (n = 66) utilized surveys, and 70% (n = 57) employed ML for common prediction tasks. Although the number of studies in ML and SDH is growing rapidly, only a few studies used ML to improve causal inference, curate data, or identify social bias in predictions (i.e., algorithmic fairness).
conclusionsWhile ML equips researchers with new ways to measure health outcomes and their determinants from non-conventional sources such as text, audio, and image data, most studies still rely on traditional surveys. Although there are no guarantees that ML will lead to better social epidemiological research, the potential for innovation in SDH research is evident as a result of harnessing the predictive power of ML for causality, data curation, or algorithmic fairness.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.