ArticleScientific reports2024
Impact of artificial intelligence assistance on pulmonary nodule detection and localization in chest CT: a comparative study among radiologists of varying experience levels.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.
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Who cites it
19 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Innovative technologies and their clinical prospects for early lung cancer screening.Clinical and experimental medicine · 2025Pooled it
- Diagnostic performance of commercial AI systems versus participating radiologists for pulmonary nodule detection in routine clinical practice.Japanese journal of radiology · 2026Article
- Impact of CT slice thickness reduction algorithm on AI-based lung nodule detection in chest CTs of colorectal cancer patients.Quantitative imaging in medicine and surgery · 2026Article
- Dynamic Convolution Enhanced Attention Network for Pulmonary Nodule Detection.Journal of imaging · 2026Article
- Scientific evidence of commercial artificial intelligence products for pulmonary nodule assessment on CT scans: a systematic review.European radiology · 2026Article
- Risk prediction of non-small cell lung cancer in patients with pulmonary nodules: a single-center cohort study based on six machine learning algorithms.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Article
- [Artificial intelligence in surgical disciplines: Clinical application, advantages, and potential-a Delphi expert consensus].Urologie (Heidelberg, Germany) · 2026Article
- Eye tracking as a tool to quantify the effects of CAD display on radiologists' interpretation of chest radiographs.European journal of radiology open · 2026Article
- Artificial Intelligence Applications in Body MRI: Opportunities and Limitations.Journal of magnetic resonance imaging : JMRI · 2026Article
- Applying artificial intelligence to ensure high quality and equitable lung cancer screening.Translational lung cancer research · 2026Review
- Imaging and characterization of pulmonary nodules in children with solid tumors: what makes a pulmonary nodule a metastasis?Pediatric radiology · 2026Review
- Comparison of three commercial AI tools for detection and malignancy assessment of incidental lung nodules.Frontiers in medicine · 2026Article
- Casting wider than U-Nets: evaluating the role of novel machine learning applications in radiation therapy.BJR artificial intelligence · 2026Review
- Nocturnal blood pressure burden: towards a better understanding of the OSA-hypertension relationship.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2025Article
- Early Detection of Lung Cancer: A Review of Innovative Milestones and Techniques.Journal of clinical medicine · 2025Review
- [Influence of artificial intelligence on decisions in radiology using the example of lung cancer screening].Radiologie (Heidelberg, Germany) · 2025Article
- Narrative review of the application of artificial intelligence-related technologies in the diagnosis of pulmonary nodules with recommendations for clinical practice and future research.Journal of thoracic disease · 2025Review
- Performance Evaluation of Four Deep Learning-Based CAD Systems and Manual Reading for Pulmonary Nodules Detection, Volume Measurement, and Lung-RADS Classification Under Varying Radiation Doses and Reconstruction Methods.Diagnostics (Basel, Switzerland) · 2025Article
- Diagnostic accuracy of serum biomarkers MMP11 and SPP1 in non-small cell lung cancer: an analysis of sensitivity, specificity, and area under the curve.Translational lung cancer research · 2025Article
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Authors and funding
15 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The study aimed to evaluate the impact of AI assistance on pulmonary nodule detection rates among radiology residents and senior radiologists, along with assessing the effectiveness of two different commercialy available AI software systems in improving detection rates and LungRADS classification in chest CT. The study cohort included 198 participants with 221 pulmonary nodules. Residents' mean detection rate increased significantly from 64 to 77% with AI assist, while seniors' detection rate remained largely unchanged (85% vs. 86%). Residents showed significant improvement in segmental nodule localization with AI assistance, seniors did not. Software 2 slightly outperformed software 1 in increasing detection rates (67-77% vs. 80-86%), but neither significantly affected LungRADS classification. The study suggests that clinical experience mitigates the need for additional AI software, with the combination of CAD with residents being the most beneficial approach. Both software systems performed similarly, with software 2 showing a slightly higher but non-significant increase in detection rates.
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