Machine learning approaches to the social determinants of health in the health and retirement study
Datos Bibliográficos
| ID | 15742159 |
|---|---|
| Autores | Benjamin Seligman (0000-0002-8223-5924, University of California, Los Angeles, autor de correspondencia), Shripad Tuljapurkar (0000-0001-5549-4245, Stanford University), D H Rehkopf (0000-0002-7597-6513, Stanford University) |
| Año | 2017 |
| Volumen | 4 |
| Páginas | 95-99 |
| Fecha de publicación | 2017-11-21 |
| Peer Reviewed | Sí |
| Open Access | Sí |
| Tipo | ARTICLE |
| Revista | SSM - Population Health (JOURNAL) |
| Identificadores de la revista | ISSN: 2352-8273 • E-ISSN: 2352-8273 |
| Editorial | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.ssmph.2017.11.008 |
| PMID | 29349278 |
| OpenAlex | W2770256320 |
| Idioma | EN |
| Citas recibidas | 8 |
| Referencias citadas | 28 |
Some of the machine learning methods do not improve prediction or fit beyond simpler models, however, neural networks performed well. The predictors identified across models suggest underlying social factors that are important predictors of biological indicators of chronic disease, and that the non-linear and interactive relationships between variables fundamental to the neural network approach may be important to consider
Artificial neural network · Interpretability · Linear model · Linear regression · Machine learning · Pathology · Public health · Random forest · Regression · Regression analysis · Social determinants of health · Statistics · Computer Science · Global Health Care Issues · Health disparities and outcomes · Health, Environment, Cognitive Aging · Mathematics · Medicine · Artificial Intelligence
Social Determinants of Mental Health
Transforming Mortality Prediction
Inequities in Mental Health Care Facing Racialized Immigrant Older Adults With Mental Disorders Despite Universal Coverage
Racial and Ethnic Disparities in Health Outcomes Among Long-Term Survivors of Childhood Cancer
Using machine learning to understand determinants of IUD use in India
Application of machine learning to understand child marriage in India
Machine learning in social epidemiology
Predicting women's height from their socioeconomic status
The Elements of Statistical Learning
Recursive partitioning for heterogeneous causal effects
DNA methylation age of human tissues and cell types
Regularization Paths for Generalized Linear Models via Coordinate Descent
The Spread of Obesity in a Large Social Network over 32 Years
Random Forests
Bayesian Model Selection in Social Research
Big Data
| Obras citantes distintas | 8 |
|---|---|
| Citas por año | 1 |
| Intervalo de citas | 2018 - 2025 (8) |
| Velocidad de citación | recent |
| Altamente citado | No |
| Tipos de cita | Neutras: 8 |