机器学习预测美国印第安人和阿拉斯加原住民的痴呆症:一个回顾性队列研究
Kayleen Ports1, Jiahui Dai1, Kyle Conniff2
1Department of Epidemiology & Biostatistics, Joe C. Wen School of Population & Public Health, Susan and Henry Samueli College of Health Sciences, University of California, Irvine, 856 Health Sciences Quad, Irvine, CA 92697-7550, USA.
Lancet regional health. Americas
|March 4, 2025
概括
机器学习模型可以使用电子健康记录预测美国印第安人和阿拉斯加土著成年人的痴呆风险. 这些工具可以帮助识别需要早期干预的个体,以获得更好的健康结果.
科学领域:
- 老年学是一门学科.
- 医疗信息学 医疗信息学
- 机器学习 机器学习
背景情况:
- 痴呆症在美国印第安人和阿拉斯加原住民 (AI/AN) 社区中构成越来越大的挑战.
- 现有的机器学习模型用于痴呆风险预测尚未为AI/AN人群开发或验证.
研究的目的:
- 开发和验证AI/AN个人的两年痴呆风险预测模型.
- 利用来自印度卫生服务 (IHS) 和部落卫生服务的电子健康记录 (EHR) 数据.
主要方法:
- 利用了来自IHS的七年电子健康记录数据 (2007-2013财年).
- 评估了四种机器学习算法:逻辑回归,LASSO,随机森林和XGBoost.
- 使用接收器操作特征曲线 (AUC) 下面的面积来评估模型性能.
主要成果:
- 该研究包括17,398名65岁以上的AI/AN成年人,其中3.5%在两年内被诊断患有痴呆症.
- 使用后勤回归,LASSO和XGBoost的扩展模型表现出可比性能,AUC约为0.82-0.83.
- 顶级模型确定了15个关键预测因素,包括新的因素,如服务利用率.
结论:
- 机器学习模型有效地使用EHR数据预测AI/AN老年人的两年痴呆风险.
- 这些预测模型可以帮助IHS和部落卫生临床医生在风险人群的早期识别和干预.
- 这些发现支持AI/AN社区内改善护理协调和及时管理痴呆症.
更多相关视频
09:38Generalized Psychophysiological Interaction PPI Analysis of Memory Related Connectivity in Individuals at Genetic Risk for Alzheimer's Disease
Published on: November 14, 2017
14.8K
06:23The 4 Mountains Test: A Short Test of Spatial Memory with High Sensitivity for the Diagnosis of Pre-dementia Alzheimer's Disease
Published on: October 13, 2016
32.1K
相关概念视频
01:30Dementia
87
Dementia is a collective term for cognitive disorders primarily affecting memory, thinking, and reasoning. It is not a specific disease but a syndrome, with Alzheimer's disease being the most common cause, accounting for approximately 60-80% of cases. Other types include vascular dementia, Lewy body dementia, and frontotemporal dementia. Dementia affects millions worldwide, particularly older adults, though it is not a normal part of aging.
The progression of dementia is generally gradual....
The progression of dementia is generally gradual....
87
01:26Alzheimer's Disease: Overview
418
Alzheimer's Disease (AD) is a continually advancing neurodegenerative disorder, distinguished by escalating memory loss, cognitive dysfunction, and dementia. The disease unfolds in three stages: preclinical, mild cognitive impairment (MCI), and dementia. Its onset is insidious, and the progression gradual, with the cause not well explained by other disorders.
The clinical diagnosis of AD hinges on the presence of memory and other cognitive impairments. Biomarkers, such as changes in Aβ...
The clinical diagnosis of AD hinges on the presence of memory and other cognitive impairments. Biomarkers, such as changes in Aβ...
418