A recent study led by the University of California, Irvine, reveals that machine learning algorithms can effectively predict two-year dementia risk among American Indian and Alaska Native elders. This research, published in The Lancet Regional Health—Americas, highlights the potential of AI to address health disparities in these historically underserved communities.
The study utilized electronic health records to develop predictive models, identifying several new predictors for dementia diagnosis. These findings are particularly significant given the projected increase in the population of older American Indian and Alaska Native adults, which is expected to nearly triple between 2020 and 2060. Dementia, a leading cause of disability and mortality in this age group, poses a growing concern.
Luohua Jiang, a professor of epidemiology and biostatistics at UC Irvine, emphasized the importance of these findings for public health researchers, clinicians, and policymakers. “If future studies confirm these results, our findings could prove valuable to the Indian Health Service and Tribal health clinicians in identifying high-risk individuals, facilitating timely interventions, and improving care coordination,” Jiang stated.
The societal impacts of dementia extend beyond the affected individuals, taking an emotional toll on family members and incurring substantial medical expenses. By leveraging AI, healthcare systems serving resource-limited populations can enhance efficiency, accuracy, and scalability in analyzing large datasets, ultimately improving care for vulnerable communities.
See: “AI effectively predicts dementia risk in American Indian/Alaska Native elders” (April 2, 2025)
