China CDC weekly · 2026
Bibliometric and Content Analysis of Artificial Intelligence in Smoking Cessation - Worldwide, 1982-2026.
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
He Aaron Wan Jia, Cheung Ferrina Hoi Yan, Shao Yuna, Li Gen, Xie Xiaoyun, Chan Sophia Siu Chee
Аннотация
WHAT IS ALREADY KNOWN ABOUT THIS TOPIC?: Tobacco use remains a major public health challenge and the leading preventable cause of death worldwide. Artificial intelligence is increasingly applied in smoking cessation research, but its overall thematic landscape and development trends have not been systematically described.
WHAT IS ADDED BY THIS REPORT?: This bibliometric and content analysis identified 1,728 publications on artificial intelligence (AI) in smoking cessation from inception to March 5, 2026. Research output increased markedly after 2017, with intervention as the dominant domain, while prediction and diagnosis emerged as closely related AI areas and monitoring remained substantially underexplored.
WHAT ARE THE IMPLICATIONS FOR PUBLIC HEALTH PRACTICE?: AI has strong potential to enhance tobacco control through digital interventions, predictive analytics, diagnostic support, and longitudinal monitoring. Expanding monitoring applications and strengthening trustworthy governance of AI may help improve smoking cessation strategies and support global tobacco control goals.
WHAT IS ADDED BY THIS REPORT?: This bibliometric and content analysis identified 1,728 publications on artificial intelligence (AI) in smoking cessation from inception to March 5, 2026. Research output increased markedly after 2017, with intervention as the dominant domain, while prediction and diagnosis emerged as closely related AI areas and monitoring remained substantially underexplored.
WHAT ARE THE IMPLICATIONS FOR PUBLIC HEALTH PRACTICE?: AI has strong potential to enhance tobacco control through digital interventions, predictive analytics, diagnostic support, and longitudinal monitoring. Expanding monitoring applications and strengthening trustworthy governance of AI may help improve smoking cessation strategies and support global tobacco control goals.