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Chencui Huang

Showing results (61-70 of 106) with videos related to

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International Journal of Endocrinology|April 1, 2021
Different Appearance of Chest CT Images of T2DM and NDM Patients with COVID-19 Pneumonia Based on an Artificial Intelligent Quantitative MethodShan Lu, Zhiheng Xing, Shiyu Zhao, et al.
Journal of Neurology|August 11, 2022
Identification of high-risk intracranial plaques with 3D high-resolution magnetic resonance imaging-based radiomics and machine learningHongxia Li, Jia Liu, Zheng Dong, et al.
European Journal of Radiology|February 5, 2023
Distinguishing multiple primary lung cancers from intrapulmonary metastasis using CT-based radiomicsMei Huang, Qinmei Xu, Mu Zhou, et al.
Diagnostics (Basel, Switzerland)|December 11, 2025
Multimodal-Imaging-Based Interpretable Deep Learning Framework for Distinguishing Brucella from Tuberculosis Spondylitis: A Dual-Center StudyMayidili Nijiati, Mei Zhang, Chencui Huang, et al.
The British Journal of Radiology|July 2, 2023
Radiomics and Ki-67 index predict survival in clear cell renal cell carcinomaTong Zhang, Ying Ming, Jingxu Xu, et al.
Frontiers in Pediatrics|March 31, 2022
A Deep-Learning Aided Diagnostic System in Assessing Developmental Dysplasia of the Hip on Pediatric Pelvic RadiographsWeize Xu, Liqi Shu, Ping Gong, et al.
Journal of Thoracic Disease|January 12, 2026
Biphasic quantitative CT to classify a residual volume-defined subclinical gas-trapping phenotype: development and internal validation of a multivariable modelFengzhi Li, Qi Liu, Yijin Zan, et al.
Journal of Oncology|March 3, 2023
Integrative Nomogram of Computed Tomography Radiomics, Clinical, and Tumor Immune Features for Analysis of Disease-Free Survival of NSCLC Patients with SurgeryDianhui Xiu, Yan Mo, Chaohui Liu, et al.
Insights Into Imaging|January 25, 2024
Preoperative CT-based deep learning radiomics model to predict lymph node metastasis and patient prognosis in bladder cancer: a two-center studyRui Sun, Meng Zhang, Lei Yang, et al.
Cancer Imaging : the Official Publication of the International Cancer Imaging Society|March 11, 2025
A CT-based interpretable deep learning signature for predicting PD-L1 expression in bladder cancer: a two-center studyXiaomeng Han, Jing Guan, Li Guo, et al.
Pageof 11

Showing results (61-70 of 106) with videos related to

Sort By:
Pageof 11
International Journal of Endocrinology|April 1, 2021
Different Appearance of Chest CT Images of T2DM and NDM Patients with COVID-19 Pneumonia Based on an Artificial Intelligent Quantitative MethodShan Lu, Zhiheng Xing, Shiyu Zhao, et al.
Journal of Neurology|August 11, 2022
Identification of high-risk intracranial plaques with 3D high-resolution magnetic resonance imaging-based radiomics and machine learningHongxia Li, Jia Liu, Zheng Dong, et al.
European Journal of Radiology|February 5, 2023
Distinguishing multiple primary lung cancers from intrapulmonary metastasis using CT-based radiomicsMei Huang, Qinmei Xu, Mu Zhou, et al.
Diagnostics (Basel, Switzerland)|December 11, 2025
Multimodal-Imaging-Based Interpretable Deep Learning Framework for Distinguishing Brucella from Tuberculosis Spondylitis: A Dual-Center StudyMayidili Nijiati, Mei Zhang, Chencui Huang, et al.
The British Journal of Radiology|July 2, 2023
Radiomics and Ki-67 index predict survival in clear cell renal cell carcinomaTong Zhang, Ying Ming, Jingxu Xu, et al.
Frontiers in Pediatrics|March 31, 2022
A Deep-Learning Aided Diagnostic System in Assessing Developmental Dysplasia of the Hip on Pediatric Pelvic RadiographsWeize Xu, Liqi Shu, Ping Gong, et al.
Journal of Thoracic Disease|January 12, 2026
Biphasic quantitative CT to classify a residual volume-defined subclinical gas-trapping phenotype: development and internal validation of a multivariable modelFengzhi Li, Qi Liu, Yijin Zan, et al.
Journal of Oncology|March 3, 2023
Integrative Nomogram of Computed Tomography Radiomics, Clinical, and Tumor Immune Features for Analysis of Disease-Free Survival of NSCLC Patients with SurgeryDianhui Xiu, Yan Mo, Chaohui Liu, et al.
Insights Into Imaging|January 25, 2024
Preoperative CT-based deep learning radiomics model to predict lymph node metastasis and patient prognosis in bladder cancer: a two-center studyRui Sun, Meng Zhang, Lei Yang, et al.
Cancer Imaging : the Official Publication of the International Cancer Imaging Society|March 11, 2025
A CT-based interpretable deep learning signature for predicting PD-L1 expression in bladder cancer: a two-center studyXiaomeng Han, Jing Guan, Li Guo, et al.
Pageof 11