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使用人工智能进行的信息病理学研究的系统审查:社交媒体上有关HIV暴露前预防的帖子

Emiko Kamitani¹, Julia B DeLuca, Yuko Mizuno

¹Division of HIV Prevention, U.S. Centers for Disease Control and Prevention, Atlanta, Georgia, United States 30329-4027.

AIDS (London, England)

|March 31, 2025

概括

人工智能 (AI) 可以通过处理关于艾滋病毒暴露前预防 (PrEP) 的社交媒体数据来增强信息学. 这种方法可以实时识别社区关注的问题和需要HIV预防干预的领域.

科学领域:

公共卫生信息学公共卫生信息学
数字流行病学数字流行病学
社交媒体分析

背景情况:

传染病学利用电子数据来追踪健康信息的分布.
社交媒体平台产生了大量与公共卫生相关的用户生成内容.
艾滋病毒暴露前预防 (PrEP) 是预防艾滋病毒的关键生物医学干预措施.

研究的目的:

探索人工智能 (AI) 在信息学中的应用,以分析与艾滋病毒暴露前预防 (PrEP) 相关的社交媒体数据.
评估人工智能如何增强社交媒体帖子的处理,以了解与PrEP相关的公共卫生问题.

主要方法:

以英语出版的信息学研究的系统综述.
搜索了美国疾病控制和预防中心的预防研究综合数据库.
包括使用人工智能处理关于PrEP的社交媒体帖子的研究;提取的数据和偏见风险评估.

主要成果:

八项研究分析了超过5890万条关于PrEP的社交媒体帖子.
确定了常见的PrEP主题 (例如,吸收障碍),公共卫生问题 (例如,错误信息) 和地理热点.
发现人工智能处理的社交媒体数据可以预测艾滋病毒趋势并确定需要干预的领域.

结论:

社交媒体为与PrEP相关的担忧和社区需求提供实时洞察力.
人工智能显著加速和增强对大规模社交媒体数据的分析,以促进公共卫生.
研究结果表明,人工智能驱动的传染病学可以指导针对性的艾滋病毒预防策略.

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