Science Editor, Medical Science Monitor, International Scientific Information, Inc., Melville, NY, USA.
Med Sci Monit. 2023 Jun 1;29:e941209. doi: 10.12659/MSM.941209.
Artificial intelligence (AI), or machine learning, is an ancient concept based on the assumption that human thought and reasoning can be mechanized. AI techniques have been used in diagnostic medicine for several decades, particularly in image analysis and clinical diagnosis. During the COVID-19 pandemic, AI was critical in genome sequencing, drug and vaccine development, identifying disease outbreaks, monitoring disease spread, and tracking viral variants. AI-driven approaches complement human-curated ones, including traditional public health surveillance. Preparation for future pandemics will require the combined efforts of collaborative surveillance networks, which currently include the US Centers for Disease Control and Prevention (CDC) Center for Forecasting and Outbreak Analytics and the World Health Organization (WHO) Hub for Pandemic and Epidemic Intelligence, which will use AI combined with international cooperation to implement AI in surveillance programs. This Editorial aims to provide an update on the uses and limitations of AI in infectious disease surveillance and pandemic preparedness.
人工智能(AI)或机器学习是一个古老的概念,其基于这样一个假设,即人类的思维和推理可以机械化。几十年来,AI 技术一直被应用于诊断医学,特别是在图像分析和临床诊断方面。在 COVID-19 大流行期间,AI 在基因组测序、药物和疫苗开发、识别疾病爆发、监测疾病传播和跟踪病毒变体方面发挥了关键作用。AI 驱动的方法补充了人类策划的方法,包括传统的公共卫生监测。为未来的大流行做准备需要协作监测网络的共同努力,目前这些网络包括美国疾病控制与预防中心(CDC)的预测和疫情分析中心以及世界卫生组织(WHO)的大流行病和传染病情报中心,这些中心将利用 AI 并结合国际合作将 AI 应用于监测计划。本社论旨在提供有关 AI 在传染病监测和大流行准备中的用途和局限性的最新信息。
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