ArticleFrontiers in public health2024
Research on the impact of artificial intelligence technology on urban public health resilience.
Article in Frontiers in public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Opportunities and challenges of artificial intelligence in public health: a systematic review on technological efficacy, ethical dilemmas, and governance pathways.Frontiers in public health · 2025Pooled it
- Evaluating the impact of artificial intelligence development on urban resilience: Evidence from Chinese cities.iScience · 2026Article
- Corporate climate risk and public health disclosure: does digital transformation matter?Frontiers in public health · 2026Article
- Enhancing Diagnostic Infrastructure Through Innovation-Driven Technological Capacity in Healthcare.Healthcare (Basel, Switzerland) · 2025Article
- The impact of the sports industry on the development of the health industry: an exploration of mediating and threshold effects.Frontiers in public health · 2025Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Urban public health resilience has become a critical focus in the transition to high-quality development, especially in addressing increasing public health challenges. This study explores the role of artificial intelligence (AI) technology in enhancing urban public health resilience across 284 Chinese cities from 2011 to 2021. Using a comprehensive index based on resistance, recovery, and innovation dimensions, the study quantifies AI technology levels through patent applications and authorizations, further disaggregating these into invention, utility model, and design patents. A two-way fixed effects regression model and spatial econometric models are employed to analyze the direct and spillover effects of AI on urban public health systems. The results demonstrate that AI technology significantly enhances resilience by improving resource allocation and response efficiency, with stronger impacts observed in eastern and central regions compared to western regions, where economic and technological capacities are weaker. Spatial analysis reveals significant positive spillover effects, particularly from patent authorizations, which enhance public health resilience in neighboring cities through cross-regional collaboration and resource sharing. Despite these advancements, regional disparities in economic development and technological infrastructure limit AI's broader impact, underscoring the need for targeted policies, enhanced funding, and interdisciplinary training to bridge the digital divide. The findings highlight AI's transformative potential in fostering urban public health resilience and call for sustained investment and collaboration to maximize its benefits.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.