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Narrative review: the research advances of artificial intelligence in the prediction of pulmonary nodule growth
0
Zitationen
9
Autoren
2026
Jahr
Abstract
AI, particularly deep learning (DL) combined with quantitative radiomics and radiogenomics, shows promise for noninvasive prediction of pulmonary nodule growth. Future work should focus on multicenter prospective validation, standardized growth endpoints, low-dose protocols, multimodal data integration, and explainable, federated, generative AI to improve robustness, transparency, and data privacy. In addition, seamless PACS integration and explicit balancing of sensitivity, specificity and overdiagnosis are essential. Ultimately, validated AI models may enable more accurate, personalized surveillance while reducing radiation exposure and resource burden.
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