ArticleScientific reports2025
Cost-effectiveness of chest radiography using artificial intelligence for lung cancer screening in South Korea.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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
1 citing paper in PubMed.
- Assessing the Value for Money of AI-Assisted Technologies for Older Adults: Scoping Review of Economic Evaluations.Journal of medical Internet research · 2026Article
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Authors and funding
8 authors.
Funding
Abstract
Artificial intelligence (AI) shows promise in improving the accuracy and efficiency of lung cancer screening, but its economic value remains uncertain. We developed a decision-analytic model combining a decision tree and Markov model to evaluate five screening strategies in South Korea: no screening, chest X-ray (CXR), AI-assisted CXR, low-dose computed tomography (LDCT), and AI-assisted LDCT. We simulated hypothetical cohorts of 10,000 individuals, stratified by age group and smoking status to reflect the Korean population distribution, and projected their lifetime costs and quality-adjusted life years (QALYs). Analyses applied a 4.5% discount rate and a willingness-to-pay (WTP) threshold of $32,409.9 per QALY. AI-assisted CXR produced incremental cost-effectiveness ratio (ICER) of $8679-$10,030 per QALY, demonstrating cost-effectiveness across all age groups. CXR alone was less favorable, and LDCT-based strategies exceeded the willingness-to-pay (WTP) threshold. These findings suggest AI-assisted CXR offers a scalable, economically viable strategy for lung cancer screening, supporting its integration into national programs.
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