Long, Y.; Li, Y.; Zheng, Y.; Lin, W.; Qing, H.; Zhou, P.; Liu, J.
Quantitative Measures of Pure Ground-Glass Nodules from an Artificial Intelligence Software for Predicting Invasiveness of Pulmonary Adenocarcinoma on Low-Dose CT: A Multicenter Study. Biomedicines 2025, 13, 1600.
https://doi.org/10.3390/biomedicines13071600
AMA Style
Long Y, Li Y, Zheng Y, Lin W, Qing H, Zhou P, Liu J.
Quantitative Measures of Pure Ground-Glass Nodules from an Artificial Intelligence Software for Predicting Invasiveness of Pulmonary Adenocarcinoma on Low-Dose CT: A Multicenter Study. Biomedicines. 2025; 13(7):1600.
https://doi.org/10.3390/biomedicines13071600
Chicago/Turabian Style
Long, Yu, Yong Li, Yongji Zheng, Wei Lin, Haomiao Qing, Peng Zhou, and Jieke Liu.
2025. "Quantitative Measures of Pure Ground-Glass Nodules from an Artificial Intelligence Software for Predicting Invasiveness of Pulmonary Adenocarcinoma on Low-Dose CT: A Multicenter Study" Biomedicines 13, no. 7: 1600.
https://doi.org/10.3390/biomedicines13071600
APA Style
Long, Y., Li, Y., Zheng, Y., Lin, W., Qing, H., Zhou, P., & Liu, J.
(2025). Quantitative Measures of Pure Ground-Glass Nodules from an Artificial Intelligence Software for Predicting Invasiveness of Pulmonary Adenocarcinoma on Low-Dose CT: A Multicenter Study. Biomedicines, 13(7), 1600.
https://doi.org/10.3390/biomedicines13071600
