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Author

Fengmei Qin

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Aug 2026

Classification of Invasiveness and Prediction of Ki-67 Expression Level in Pulmonary Ground-Glass Nodules Based on CT Images Using Artificial Intelligence

This work aimed to accurately determine the invasiveness level of pulmonary ground-glass nodules (GGNs) preoperatively and to adjust personalized treatment plans accordingly. This paper presents a multi-task artificial intelligence framework to simultaneously perform three-class invasiveness classification of GGNs and...

Hongda Pan, Si-Yuan Tang, Naiyu Wang et al. · 0 citations

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