Wanming Hu

1.5k total citations
78 papers, 944 citations indexed

About

Wanming Hu is a scholar working on Oncology, Genetics and Molecular Biology. According to data from OpenAlex, Wanming Hu has authored 78 papers receiving a total of 944 indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Oncology, 24 papers in Genetics and 18 papers in Molecular Biology. Recurrent topics in Wanming Hu's work include Glioma Diagnosis and Treatment (24 papers), Cancer Immunotherapy and Biomarkers (10 papers) and Radiomics and Machine Learning in Medical Imaging (9 papers). Wanming Hu is often cited by papers focused on Glioma Diagnosis and Treatment (24 papers), Cancer Immunotherapy and Biomarkers (10 papers) and Radiomics and Machine Learning in Medical Imaging (9 papers). Wanming Hu collaborates with scholars based in China, United States and Hong Kong. Wanming Hu's co-authors include Yuanzhong Yang, Jing Zeng, Wenzhuo He, Chang Jiang, Liangping Xia, Lin Yang, Qiankun Xie, Ke Sai, Pengfei Kong and Weiyuan Wang and has published in prestigious journals such as Nature Communications, Journal of Clinical Oncology and The Journal of Clinical Endocrinology & Metabolism.

In The Last Decade

Wanming Hu

72 papers receiving 935 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Wanming Hu China 17 417 215 192 190 158 78 944
Laura Mariuzzi Italy 21 269 0.6× 273 1.3× 195 1.0× 171 0.9× 170 1.1× 90 1.3k
Robyn D. Gartrell United States 18 472 1.1× 221 1.0× 297 1.5× 118 0.6× 103 0.7× 45 842
Julia Gilhodes France 19 459 1.1× 513 2.4× 309 1.6× 170 0.9× 173 1.1× 38 1.2k
Arivarasan Karunamurthy United States 14 337 0.8× 262 1.2× 236 1.2× 140 0.7× 81 0.5× 50 1.1k
Roberta Depenni Italy 18 679 1.6× 270 1.3× 125 0.7× 306 1.6× 189 1.2× 58 1.1k
Triantafyllia Κoletsa Greece 16 194 0.5× 172 0.8× 140 0.7× 141 0.7× 61 0.4× 104 844
Lidia Gatto Italy 21 342 0.8× 326 1.5× 115 0.6× 450 2.4× 334 2.1× 83 1.2k
Eckhard Fiedler Germany 18 332 0.8× 217 1.0× 108 0.6× 145 0.8× 127 0.8× 39 1.0k
Yoichi Tani Japan 18 381 0.9× 338 1.6× 135 0.7× 167 0.9× 44 0.3× 50 960
Bolette L. Caron United States 11 341 0.8× 208 1.0× 104 0.5× 317 1.7× 166 1.1× 12 843

Countries citing papers authored by Wanming Hu

Since Specialization
Citations

This map shows the geographic impact of Wanming Hu's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Wanming Hu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wanming Hu more than expected).

Fields of papers citing papers by Wanming Hu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Wanming Hu. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Wanming Hu. The network helps show where Wanming Hu may publish in the future.

Co-authorship network of co-authors of Wanming Hu

This figure shows the co-authorship network connecting the top 25 collaborators of Wanming Hu. A scholar is included among the top collaborators of Wanming Hu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Wanming Hu. Wanming Hu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Wang, Xiaofei, Hao Duan, Wanming Hu, et al.. (2025). Joint modeling histology and molecular markers for cancer classification. Medical Image Analysis. 102. 103505–103505.
2.
3.
Hu, Wanming, et al.. (2024). Alterations in intratumoral and peripheral immune status in recurrent gliomas and their prognostic implications for patients underwent reoperation. International Immunopharmacology. 140. 112797–112797. 2 indexed citations
4.
Duan, Hao, Zhenqiang He, Yukun Chen, et al.. (2024). Long-term survival after local immunotherapy for malignant gliomas: a retrospective study with 20 years follow-up. BMC Immunology. 25(1). 83–83.
5.
Xie, Yuan, Guangyin Zhao, Zhen Zeng, et al.. (2024). Effect of the mRNA decapping enzyme scavenger (DCPS) inhibitor RG3039 on glioblastoma. Journal of Translational Medicine. 22(1). 880–880. 1 indexed citations
6.
7.
Li, Hainan, Juan Li, Jiangfen Zhou, et al.. (2023). Lorlatinib for ALK‐fused, infant‐type hemispheric glioma with lung metastasis: a case report. Annals of Clinical and Translational Neurology. 10(5). 836–841. 5 indexed citations
8.
Chen, Jiehong, Shuxin Sun, Wenfeng Liu, et al.. (2022). Disruption of β-catenin-mediated negative feedback reinforces cAMP-induced neuronal differentiation in glioma stem cells. Cell Death and Disease. 13(5). 493–493. 12 indexed citations
9.
Cheng, Jun, Yize Mao, Wanming Hu, et al.. (2022). Multimodal data analysis reveals that pancreatobiliary-type ampullary adenocarcinoma resembles pancreatic adenocarcinoma and differs from cholangiocarcinoma. Journal of Translational Medicine. 20(1). 272–272. 5 indexed citations
10.
Hu, Wanming, Li Yuan, Xinke Zhang, et al.. (2022). Development and validation of an RNA sequencing panel for gene fusions in soft tissue sarcoma. Cancer Science. 113(5). 1843–1854. 5 indexed citations
11.
Liu, Pan, et al.. (2022). PTBP1 is a Novel Poor Prognostic Factor for Glioma. BioMed Research International. 2022(1). 7590997–7590997. 6 indexed citations
12.
Hu, Wanming, R. Lambo, Zhicheng Zhang, et al.. (2021). Weakly Supervised Framework for Cancer Region Detection of Hepatocellular Carcinoma in Whole-Slide Pathologic Images Based on Multiscale Attention Convolutional Neural Network. American Journal Of Pathology. 192(3). 553–563. 16 indexed citations
13.
Sun, Shuxin, Yang Liu, Chaobin He, et al.. (2021). Combining NanoKnife with M1 oncolytic virus enhances anticancer activity in pancreatic cancer. Cancer Letters. 502. 9–24. 36 indexed citations
14.
Mao, Yize, Weisheng Cheng, Qiuxia Yang, et al.. (2021). The enhanced cell cycle related to the response to adjuvant therapy in pancreatic ductal adenocarcinoma. Genomics. 114(1). 95–106. 1 indexed citations
15.
Li, De‐Pei, Wanming Hu, Xiaoping Lin, et al.. (2021). CARD-Associated Risk Score Features the Immune Landscape and Predicts the Responsiveness to Anti-PD-1 Therapy in IDH Wild-Type Gliomas. Frontiers in Cell and Developmental Biology. 9. 653240–653240. 2 indexed citations
16.
Zhang, Ji, et al.. (2020). Tim-3 Expression and MGMT Methylation Status Association With Survival in Glioblastoma. Frontiers in Pharmacology. 11. 584652–584652. 12 indexed citations
17.
Chen, Hong, Wanming Hu, Haoqiang He, et al.. (2019). Noninvasive assessment of H3 K27M mutational status in diffuse midline gliomas by using apparent diffusion coefficient measurements. European Journal of Radiology. 114. 152–159. 35 indexed citations
18.
Jiang, Xiaobing, Yinsheng Chen, Liping Luo, et al.. (2018). Surgical Resection of Pineal Epidermoid Cyst Contributed to Relieving Schizophrenia Symptoms. World Neurosurgery. 113. 304–307. 4 indexed citations
19.
Mao, Yize, Wanming Hu, Shuhang Xu, et al.. (2018). Intravoxel incoherent motion magnetic resonance imaging for differentiating metastatic and non-metastatic lymph nodes in pancreatic ductal adenocarcinoma. European Radiology. 28(7). 2781–2789. 15 indexed citations
20.
Wu, Chenyan, Jian-Ping Huo, Xin‐Ke Zhang, et al.. (2017). Loss of CD15 expression in clear cell renal cell carcinoma is correlated with worse prognosis in Chinese patients. Japanese Journal of Clinical Oncology. 47(12). 1182–1188. 11 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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