Multiparametric MRI‐based radiomics nomogram for predicting lymph node metastasis in early‐stage cervical cancer

…, Y Li, Y Li, M Li, G Zhang, J Qiang - Journal of Magnetic …, 2020 - Wiley Online Library
Background Lymph node metastasis (LNM) is a critical risk factor affecting treatment
strategy and prognosis in patients with early‐stage cervical cancer. Purpose To establish a …
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[PDF] researchgate.net

MR image-based radiomics to differentiate type Ι and type ΙΙ epithelial ovarian cancers

…, K Wang, G Lin, F Feng, X Wu, X Gao, J Qiang - European …, 2021 - Springer
Objectives Epithelial ovarian cancers (EOC) can be divided into type I and type II according
to etiology and prognosis. Accurate subtype differentiation can substantially impact patient …
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[PDF] researchgate.net

Standard diffusion-weighted, diffusion kurtosis and intravoxel incoherent motion MR imaging of sinonasal malignancies: correlations with Ki-67 proliferation status

Z Xiao, Y Zhong, Z Tang, J Qiang, W Qian, R Wang… - European …, 2018 - Springer
Objectives To explore the correlations of parameters derived from standard diffusion-weighted
imaging (DWI), diffusion kurtosis imaging (DKI) and intravoxel incoherent motion (IVIM) …
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[PDF] researchgate.net

MRI‐based machine learning for differentiating borderline from malignant epithelial ovarian tumors: A multicenter study

…, F Feng, J Lu, L Deng, X Wu, J Qiang… - Journal of Magnetic …, 2020 - Wiley Online Library
Background Preoperative differentiation of borderline from malignant epithelial ovarian tumors
(BEOT from MEOT) can impact surgical management. MRI has improved this assessment …
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Diagnostic performance of MR imaging in evaluating prognostic factors in patients with cervical cancer: a meta-analysis

M Xiao, B Yan, Y Li, J Lu, J Qiang - European radiology, 2020 - Springer
Objectives This study aims to determine the diagnostic performance of conventional magnetic
resonance imaging (MRI) in assessing the distance between the tumor and the internal os, …
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Prediction of platinum resistance for advanced high-grade serous ovarian carcinoma using MRI-based radiomics nomogram

H Li, S Cai, L Deng, Z Xiao, Q Guo, J Qiang, J Gong… - European …, 2023 - Springer
Objective This study aimed to explore the value of a radiomics nomogram to identify platinum
resistance and predict the progression-free survival (PFS) of patients with advanced high-…
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Noninvasive prediction of residual disease for advanced high-grade serous ovarian carcinoma by MRI-based radiomic-clinical nomogram

…, X Chen, J Zhang, S Cai, Y Li, S Zhao, J Qiang… - European …, 2021 - Springer
Objectives To develop a preoperative MRI-based radiomic-clinical nomogram for prediction
of residual disease (RD) in patients with advanced high-grade serous ovarian carcinoma (…
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Multiple instance convolutional neural network with modality-based attention and contextual multi-instance learning pooling layer for effective differentiation between …

…, R Zhang, X Zhao, J Zhang, X Wu, J Qiang… - Artificial intelligence in …, 2021 - Elsevier
Malignant epithelial ovarian tumors (MEOTs) are the most lethal gynecologic malignancies,
accounting for 90% of ovarian cancer cases. By contrast, borderline epithelial ovarian …
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Development and validation of MRI-based radiomics model to predict recurrence risk in patients with endometrial cancer: a multicenter study

…, Q Bi, Y Wang, Y Luo, F Feng, M Xiao, Y Gu, J Qiang… - European …, 2023 - Springer
Objectives To develop a fusion model based on clinicopathological factors and MRI radiomics
features for the prediction of recurrence risk in patients with endometrial cancer (EC). …
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MRI‐Based Multiple Instance Convolutional Neural Network for Increased Accuracy in the Differentiation of Borderline and Malignant Epithelial Ovarian Tumors

…, J Zhang, S Cai, X Wu, X Gao, J Qiang - Journal of Magnetic …, 2022 - Wiley Online Library
Background Preoperative differentiation of borderline from malignant epithelial ovarian
tumors (BEOT vs. MEOT) is challenging and can significantly impact surgical management. …
Save Cite Cited by 13 Related articles All 3 versions