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Quantitative Imaging in Medicine and Surgery|April 13, 2019
Quantitative radiomic model for predicting malignancy of small solid pulmonary nodules detected by low-dose CT screeningLiting Mao, Huan Chen, Mingzhu Liang, et al.
Analytical Methods : Advancing Methods and Applications|April 2, 2026
Single-enzyme-driven cascade amplification integrating target recycling and a DNA walker for highly sensitive nucleic acid detectionYizhuo Zhao, Mengying Gao, Jiabei Xing, et al.
Analytical Methods : Advancing Methods and Applications|March 18, 2024
MOF-mediated dual energy transfer nanoprobe integrated with exonuclease III amplification strategy for highly sensitive detection of DNAXiaojing Xing, Mengying Gao, Minglin Lei, et al.
European Journal of Radiology|November 27, 2021
A CT-based deep learning model for subsolid pulmonary nodules to distinguish minimally invasive adenocarcinoma and invasive adenocarcinomaXiangmeng Chen, Bao Feng, Yehang Chen, et al.
Quantitative Imaging in Medicine and Surgery|August 3, 2021
Assessing the predictive accuracy of lung cancer, metastases, and benign lesions using an artificial intelligence-driven computer aided diagnosis systemKunwei Li, Kunfeng Liu, Yinghua Zhong, et al.
European Radiology|March 28, 2020
CT image visual quantitative evaluation and clinical classification of coronavirus disease (COVID-19)Kunwei Li, Yijie Fang, Wenjuan Li, et al.
BMC Medical Imaging|May 13, 2026
Deep residual network fusing CT images and clinical variables to predict lung adenocarcinoma aggressivenessJia Peng, Wenqiang Zhong, Kunwei Li, et al.
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