Wenting Tu

1.6k total citations
58 papers, 1.1k citations indexed

About

Wenting Tu is a scholar working on Pulmonary and Respiratory Medicine, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Wenting Tu has authored 58 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Pulmonary and Respiratory Medicine, 22 papers in Artificial Intelligence and 20 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Wenting Tu's work include Lung Cancer Diagnosis and Treatment (22 papers), Radiomics and Machine Learning in Medical Imaging (18 papers) and Topic Modeling (12 papers). Wenting Tu is often cited by papers focused on Lung Cancer Diagnosis and Treatment (22 papers), Radiomics and Machine Learning in Medical Imaging (18 papers) and Topic Modeling (12 papers). Wenting Tu collaborates with scholars based in China, Hong Kong and United States. Wenting Tu's co-authors include Min Yang, Shiliang Sun, Xiaojun Chen, Shiyuan Liu, Li Fan, Zhaobin Li, Jingxuan Wang, Qiang Qu, Nikos Mamoulis and Yun Wang and has published in prestigious journals such as Expert Systems with Applications, Information Sciences and Journal of the Operational Research Society.

In The Last Decade

Wenting Tu

57 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Wenting Tu China 17 445 400 372 118 117 58 1.1k
Ricky K. Taira United States 22 626 1.4× 379 0.9× 266 0.7× 55 0.5× 91 0.8× 132 1.6k
Charles Florin United States 8 653 1.5× 177 0.4× 106 0.3× 68 0.6× 64 0.5× 10 1.1k
André Bauer Germany 20 125 0.3× 258 0.6× 113 0.3× 355 3.0× 354 3.0× 83 1.4k
Amirata Ghorbani United States 8 567 1.3× 486 1.2× 102 0.3× 27 0.2× 124 1.1× 15 1.4k
Issei Sato Japan 19 698 1.6× 83 0.2× 80 0.2× 91 0.8× 117 1.0× 75 1.2k
Catarina Moreira Portugal 15 717 1.6× 483 1.2× 101 0.3× 82 0.7× 61 0.5× 73 1.3k
Osslan Osíris Vergara Villegas Mexico 13 126 0.3× 189 0.5× 148 0.4× 50 0.4× 62 0.5× 68 590
Shintami Chusnul Hidayati Indonesia 13 255 0.6× 320 0.8× 208 0.6× 67 0.6× 72 0.6× 71 952
Mohammad Amin Morid United States 12 293 0.7× 182 0.5× 41 0.1× 59 0.5× 125 1.1× 20 774

Countries citing papers authored by Wenting Tu

Since Specialization
Citations

This map shows the geographic impact of Wenting Tu'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 Wenting Tu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wenting Tu more than expected).

Fields of papers citing papers by Wenting Tu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Wenting Tu. 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 Wenting Tu. The network helps show where Wenting Tu may publish in the future.

Co-authorship network of co-authors of Wenting Tu

This figure shows the co-authorship network connecting the top 25 collaborators of Wenting Tu. A scholar is included among the top collaborators of Wenting Tu 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 Wenting Tu. Wenting Tu 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.
Ma, Yanqing, Bing Fan, Yu Guan, et al.. (2024). CT whole lung radiomic nomogram: a potential biomarker for lung function evaluation and identification of COPD. Military Medical Research. 11(1). 14–14. 12 indexed citations
2.
Qin, Chuan, et al.. (2024). FollowAKOInvestor: Stock recommendation by hearing voices from all kinds of investors with machine learning. Expert Systems with Applications. 249. 123522–123522. 2 indexed citations
3.
Zhang, Di, Mingzi Zhang, Lu Yang, et al.. (2024). Aerodynamic Simulation of Small Airway Resistance: A New Imaging Biomarker for Chronic Obstructive Pulmonary Disease. International Journal of COPD. Volume 19. 1167–1175. 1 indexed citations
4.
Wang, Yun, Chao Cheng, Wenting Tu, et al.. (2024). Preoperative nomogram for predicting spread through air spaces in clinical-stage IA non-small cell lung cancer using 18F-fluorodeoxyglucose positron emission tomography/computed tomography. Journal of Cancer Research and Clinical Oncology. 150(4). 185–185. 6 indexed citations
5.
Wang, Yun, Yanqing Ma, Shaofeng Duan, et al.. (2024). Nomogram using intratumoral and peritumoral radiomics for the preoperative prediction of visceral pleural invasion in clinical stage IA lung adenocarcinoma. Journal of Cardiothoracic Surgery. 19(1). 307–307. 4 indexed citations
6.
Wang, Yun, et al.. (2024). CT-Based Intratumoral and Peritumoral Radiomics Nomograms for the Preoperative Prediction of Spread Through Air Spaces in Clinical Stage IA Non-small Cell Lung Cancer. Journal of Imaging Informatics in Medicine. 37(2). 520–535. 14 indexed citations
7.
Lü, Xiaomei, et al.. (2023). Ultra-low-dose spectral-detector computed tomography for the accurate quantification of pulmonary nodules: an anthropomorphic chest phantom study. Diagnostic and Interventional Radiology. 29(5). 691–703. 1 indexed citations
8.
9.
Huang, Wenjun, Zhaobin Li, Jing Zhang, et al.. (2023). Baseline whole-lung CT features deriving from deep learning and radiomics: prediction of benign and malignant pulmonary ground-glass nodules. Frontiers in Oncology. 13. 1255007–1255007. 9 indexed citations
10.
Tu, Wenting, Peng Dong, Shaofeng Duan, et al.. (2023). CT-Based Radiomic Nomogram for the Prediction of Chronic Obstructive Pulmonary Disease in Patients with Lung cancer. Academic Radiology. 30(12). 2894–2903. 10 indexed citations
11.
12.
Yang, Min, et al.. (2020). Multitask Learning and Reinforcement Learning for Personalized Dialog Generation: An Empirical Study. IEEE Transactions on Neural Networks and Learning Systems. 32(1). 49–62. 26 indexed citations
13.
Yang, Min, Wenpeng Yin, Qiang Qu, et al.. (2019). Neural Attentive Network for Cross-Domain Aspect-Level Sentiment Classification. IEEE Transactions on Affective Computing. 12(3). 761–775. 36 indexed citations
14.
Yang, Min, et al.. (2019). Discovering author interest evolution in order-sensitive and Semantic-aware topic modeling. Information Sciences. 486. 271–286. 10 indexed citations
15.
Tu, Wenting, Guangyuan Sun, Li Fan, et al.. (2019). Radiomics signature: A potential and incremental predictor for EGFR mutation status in NSCLC patients, comparison with CT morphology. Lung Cancer. 132. 28–35. 118 indexed citations
16.
17.
Fan, Li, Mengjie Fang, Wenting Tu, et al.. (2018). Radiomics Signature: A Biomarker for the Preoperative Distant Metastatic Prediction of Stage I Nonsmall Cell Lung Cancer. Academic Radiology. 26(9). 1253–1261. 9 indexed citations
18.
Fan, Li, Mengjie Fang, Di Dong, et al.. (2017). Subtype discrimination of lung adenocarcinoma manifesting as ground glass nodule based on radiomics. Zhonghua fangshexian yixue zazhi. 51(12). 912–917. 2 indexed citations
19.
Wang, Hao, et al.. (2017). Personalized location recommendation by aggregating multiple recommenders in diversity. The HKU Scholars Hub (University of Hong Kong). 23 indexed citations
20.
Tu, Wenting, et al.. (2015). Real-time detection and sorting of news on microblogging platforms. Pacific Asia Conference on Language, Information, and Computation. 462–470. 1 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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