ArticleThoracic cancer2024
Application of artificial intelligence in lung cancer screening: A real-world study in a Chinese physical examination population.
Article in Thoracic cancer, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Diagnostic accuracy of deep learning-assisted low-dose CT screening for lung cancer detection: a systematic review and meta-analysis.Diagnostic and prognostic research · 2026Article
- AI in Lung Nodules on Chest CT: Retrospective, Real-World Assessment of AI in Clinical Practice.JMIR formative research · 2026Article
- [Expert Consensus on Precision Management of Pulmonary Nodules (2026 Version)].Zhongguo fei ai za zhi = Chinese journal of lung cancer · 2026Article
- The intersection of artificial intelligence and lung nodule research: current applications and future prospects.International journal of surgery (London, England) · 2026Article
- Bangkok declarations on cancer control in Asia.The Lancet regional health. Western Pacific · 2025Review
- Precision Medicine in Lung Cancer Screening: A Paradigm Shift in Early Detection-Precision Screening for Lung Cancer.Diagnostics (Basel, Switzerland) · 2025Review
- China Protocol for early screening, precise diagnosis, and individualized treatment of lung cancer.Signal transduction and targeted therapy · 2025Review
- Editorial: Advancements and Challenges in Lung Cancer Screening, Diagnosis, and Management.Diagnostics (Basel, Switzerland) · 2025Article
- AI-Enhanced CAD in Low-Dose CT: Balancing Accuracy, Efficiency, and Overdiagnosis in Lung Cancer Screening.Thoracic cancer · 2025Article
- Application of artificial intelligence in lung cancer screening: A real-world study in a Chinese physical examination population.Thoracic cancer · 2024Article
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Authors and funding
10 authors.
Funding
Abstract
backgroundWith the rapid increase of chest computed tomography (CT) images, the workload faced by radiologists has increased dramatically. It is undeniable that the use of artificial intelligence (AI) image-assisted diagnosis system in clinical treatment is a major trend in medical development. Therefore, in order to explore the value and diagnostic accuracy of the current AI system in clinical application, we aim to compare the detection and differentiation of benign and malignant pulmonary nodules between AI system and physicians, so as to provide a theoretical basis for clinical application.
methodsOur study encompassed a cohort of 23 336 patients who underwent chest low-dose spiral CT screening for lung cancer at the Health Management Center of West China Hospital. We conducted a comparative analysis between AI-assisted reading and manual interpretation, focusing on the detection and differentiation of benign and malignant pulmonary nodules.
resultsThe AI-assisted reading exhibited a significantly higher screening positive rate and probability of diagnosing malignant pulmonary nodules compared with manual interpretation (p < 0.001). Moreover, AI scanning demonstrated a markedly superior detection rate of malignant pulmonary nodules compared with manual scanning (97.2% vs. 86.4%, p < 0.001). Additionally, the lung cancer detection rate was substantially higher in the AI reading group compared with the manual reading group (98.9% vs. 90.3%, p < 0.001).
conclusionsOur findings underscore the superior screening positive rate and lung cancer detection rate achieved through AI-assisted reading compared with manual interpretation. Thus, AI exhibits considerable potential as an adjunctive tool in lung cancer screening within clinical practice settings.
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