人工智能在老龄化和生命过程的空间流行病学和健康差异研究方面的机遇和不足。

IF 3.8 2区医学 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

Health & Place Pub Date : 2024-07-23 DOI:10.1016/j.healthplace.2024.103323

Hoda S. Abdel Magid , Michael R. Desjardins , Yingjie Hu

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引用次数: 0

摘要

已有的空间和生命历程方法帮助流行病学家和健康与医学地理学家研究个人和地区层面的决定因素对健康差异的影响。虽然这些方法很有效，但地理空间人工智能（GeoAI）的出现为在空间老龄化和生命历程研究中利用复杂的多尺度数据提供了新的机遇。本视角的目的有三：（1）回顾老龄化、生命历程和空间流行病学研究中的既定方法；（2）强调 GeoAI 为加强生命历程和老龄化研究中的健康差异研究提供的一些机会；（3）讨论在老龄化和生命历程研究中使用 GeoAI 方法的不足之处。

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Opportunities and shortcomings of AI for spatial epidemiology and health disparities research on aging and the life course

Established spatial and life course methods have helped epidemiologists and health and medical geographers study the impact of individual and area-level determinants on health disparities. While these methods are effective, the emergence of Geospatial Artificial Intelligence (GeoAI) offers new opportunities to leverage complex and multi-scalar data in spatial aging and life course research. The objective of this perspective is three-fold: (1) to review established methods in aging, life course, and spatial epidemiology research; (2) to highlight some of the opportunities offered by GeoAI for enhancing research on health disparities across life course and aging research; (3) to discuss the shortcomings of using GeoAI methods in aging and life course studies.

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