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...