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Author

Dapeng Hao

Observed names: D. Hao, Da peng Hao, Da-Peng Hao, Da-peng Hao, Da‐peng Hao, Da‑Peng Hao
ORCID: 0000-0002-4215-7116
Observed ORCIDs: 0000-0002-4215-7116, 0000-0003-3499-4106, 0000-0001-6529-399X
OpenAlex ID: A5084906172
T1 Relaxivities of Gadolinium-Based Magnetic Resonance Contrast Agents in Human Whole Blood at 1.5, 3, and 7 T
2015 · Yaqi Shen, Frank L. Goerner, et al. · Investigative Radiology · 257
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A CT-based radiomics nomogram for differentiation of renal angiomyolipoma without visible fat from homogeneous clear cell renal cell carcinoma
2019 · Pei Nie, Guangjie Yang, et al. · European Radiology · 109
Radiomics and Machine Learning With Multiparametric Preoperative MRI May Accurately Predict the Histopathological Grades of Soft Tissue Sarcomas
2019 · Hexiang Wang, Haisong Chen, et al. · Journal of Magnetic Resonance Imaging · 81
Preoperative MRI‐Based Radiomic Machine‐Learning Nomogram May Accurately Distinguish Between Benign and Malignant Soft‐Tissue Lesions: A Two‐Center Study
2020 · Hexiang Wang, Jian Zhang, et al. · Journal of Magnetic Resonance Imaging · 71
Deep learning radiomic nomogram to predict recurrence in soft tissue sarcoma: a multi-institutional study
2021 · Shunli Liu, Weikai Sun, et al. · European Radiology · 69
Radiomics nomogram for differentiating between benign and malignant soft‐tissue masses of the extremities
2019 · Hexiang Wang, Pei Nie, et al. · Journal of Magnetic Resonance Imaging · 56
Magnetic Resonance Imaging‐Based Radiomics Nomogram for Prediction of the Histopathological Grade of Soft Tissue Sarcomas: A Two‐Center Study
2021 · Ruixin Yan, Dapeng Hao, et al. · Journal of Magnetic Resonance Imaging · 54
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Soft Tissue Sarcoma: Preoperative MRI-Based Radiomics and Machine Learning May Be Accurate Predictors of Histopathologic Grade
2020 · Wenjian Xu, Dapeng Hao, et al. · American Journal of Roentgenology · 54
The radiomics-based tumor heterogeneity adds incremental value to the existing prognostic models for predicting outcome in localized clear cell renal cell carcinoma: a multicenter study
2022 · Guangjie Yang, Pei Nie, et al. · European Journal of Nuclear Medicine and Molecular Imaging · 52
A CT-based radiomics nomogram for distinguishing between benign and malignant bone tumours
2021 · Weikai Sun, Shunli Liu, et al. · Cancer Imaging · 52
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The Developmental History of the Gadolinium Chelates as Intravenous Contrast Media for Magnetic Resonance
2011 · Val M. Runge, Tao Ai, et al. · Investigative Radiology · 52
Radiomics-based machine-learning method for prediction of distant metastasis from soft-tissue sarcomas
2020 · L. Tian, D. Zhang, et al. · Clinical Radiology · 39
A CT-based radiomics nomogram for differentiation of lympho-associated benign and malignant lesions of the parotid gland
2020 · Ying-mei Zheng, Wen-jian Xu, et al. · European Radiology · 39
CT and MRI Findings of Soft Tissue Adult Fibrosarcoma in Extremities
2018 · Hexiang Wang, Pei Nie, et al. · BioMed Research International · 39
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Deep Learning Radiomics Nomogram to Predict Lung Metastasis in Soft-Tissue Sarcoma: A Multi-Center Study
2022 · Hao-yu Liang, Shi-feng Yang, et al. · Frontiers in Oncology · 30
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An MRI ‐Based Radiomic Nomogram for Discrimination Between Malignant and Benign Sinonasal Tumors
2020 · Han Zhang, Hexiang Wang, et al. · Journal of Magnetic Resonance Imaging · 29
Multi-parametric MRI-based radiomics signature for preoperative prediction of Ki-67 proliferation status in sinonasal malignancies: a two-centre study
2022 · Shucheng Bi, Jie Li, et al. · European Radiology · 27
Deep Learning Radiomics Nomogram Based on Enhanced CT to Predict the Response of Metastatic Lymph Nodes to Neoadjuvant Chemotherapy in Locally Advanced Gastric Cancer
2023 · Hao Zhong, Tongyu Wang, et al. · Annals of Surgical Oncology · 25
CT and MR imaging findings of sinonasal angiomatous polyps
2013 · Jing Zou, Fengyuan Man, et al. · European Journal of Radiology · 25
A computed tomography–based radiomics signature for predicting expression of programmed death ligand 1 in head and neck squamous cell carcinoma
2022 · Ying-mei Zheng, Ming-gang Yuan, et al. · European Radiology · 23
CT Radiomics Model for Predicting the Ki-67 Index of Lung Cancer： An Exploratory Study
2021 · Qing Fu, Shun li Liu, et al. · Frontiers in Oncology · 22
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Benign or Malignant Characterization of Soft-Tissue Tumors by Using Semiquantitative and Quantitative Parameters of Dynamic Contrast-Enhanced Magnetic Resonance Imaging
2020 · Yu Zhang, Bin Yue, et al. · Canadian Association of Radiologists Journal · 22
MRI Findings of Early Myositis Ossificans without Calcification or Ossification
2018 · Hexiang Wang, Pei Nie, et al. · BioMed Research International · 21
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Magnetic Resonance Features and Characteristic Vascular Pattern of Alveolar Soft-Part Sarcoma
2017 · Jiu-Fa Cui, Hai-Song Chen, et al. · Oncology Research and Treatment · 19
An MRI ‐Based Radiomics Nomogram to Assess Recurrence Risk in Sinonasal Malignant Tumors
2022 · Tongyu Wang, Jingwei Hao, et al. · Journal of Magnetic Resonance Imaging · 16
Works count: 85
Citation count: 1,544
H-index: 22
I10-index: 33
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