Related Experiment Video
Updated: Aug 6, 2026
12:18
A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
The Relationship between Biological Aging and Cognitive Function: A Machine Learning Model
Chongkang Ren1, Zean Li1, Jinyi Cai2
1Department of Neurosurgery, The First Bethune Hospital of Jilin University, Changchun, China.
Yonsei Medical Journal
|July 22, 2026
Summary
Phenotypic age (PhenoAge) significantly increases the risk of cognitive impairment in older adults. Machine learning models incorporating sociodemographic factors show promise for early risk screening.
Area of Science:
- Gerontology and Cognitive Science
- Biomarkers of Aging
- Public Health and Epidemiology
Background:
- The link between biological age (BA) and cognitive impairment remains unclear.
- Understanding this relationship is crucial for identifying at-risk populations.
Purpose of the Study:
- To investigate the association between biological age and cognitive impairment.
- To evaluate the predictive performance of different biological age indicators and machine learning models.
Main Methods:
- Utilized data from 2202 participants in the National Health and Nutrition Examination Survey (2011-2014).
- Calculated Klemera-Doubal method age (KDM-Age) and phenotypic age (PhenoAge).
- Employed six machine learning models and Shapley additive explanations (SHAP) for analysis.
Main Results:
- Each 1-year increase in PhenoAge correlated with higher risks for CERAD, DSST, and AFT cognitive tests (p<0.001).
- The random forest model demonstrated superior performance in predicting cognitive impairment (AUC-ROC=0.997).
- Sociodemographic factors significantly outweighed biological age indicators in predictive models.
Conclusions:
- PhenoAge serves as a valuable indicator for cognitive impairment risk in older adults.
- Integrating machine learning with sociodemographic data can enhance early risk detection.
Related Concept Videos
01:26Aging
Aging is a complex biological phenomenon influenced by various processes that affect cellular and systemic functions. Several prominent theories attempt to explain its mechanisms, highlighting cellular limitations, oxidative damage, and hormonal changes as central factors in aging.
Cellular Clock Theory
The cellular clock theory posits that the human lifespan is closely tied to the finite capacity of cells to divide, a phenomenon governed by telomeres, which are protective caps at the ends of...
Cellular Clock Theory
The cellular clock theory posits that the human lifespan is closely tied to the finite capacity of cells to divide, a phenomenon governed by telomeres, which are protective caps at the ends of...
01:30Cognitive Development During Adulthood
Cognitive development continues throughout adulthood, undergoing significant shifts across early, middle, and late stages. Individual transition occurs from adolescent idealism to pragmatic and adaptable thinking in early adulthood. During this period, individuals learn to integrate personal beliefs with the recognition that other perspectives are equally valid. Exposure to the complexities of modern society, diverse experiences, and higher education contribute to this adaptive thought process,...
01:19The Effect of Aging on Tissues
Several body functions deteriorate with age. The external signs of aging are easily identifiable. For example, the skin becomes dry, less elastic, and thins out, forming wrinkles. The skin of the face begins to appear looser due to a decrease in the levels of elastic and collagen fibers in the connective tissue. Additionally, melanin production in the hair follicle decreases with age, resulting in gray hair. Moreover, the senses of sight and hearing decline, so glasses and hearing aids may...
01:29Alzheimer Disease l: Introduction
Alzheimer disease is a chronic, progressive, and irreversible neurodegenerative disorder and the most common cause of dementia in older adults. It leads to gradual neuronal loss, causing cognitive decline, behavioral changes, and loss of functional independence.Risk Factors and EtiologyThe disease is multifactorial. Age is the strongest risk factor, with prevalence doubling every 5 years after age 65. Genetic factors include mutations in genes such as APP, PSEN1, and PSEN2, which are associated...