Daoying Geng

752 total citations · 1 hit paper
9 papers, 504 citations indexed

About

Daoying Geng is a scholar working on Neurology, Pulmonary and Respiratory Medicine and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Daoying Geng has authored 9 papers receiving a total of 504 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Neurology, 4 papers in Pulmonary and Respiratory Medicine and 3 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Daoying Geng's work include Long-Term Effects of COVID-19 (3 papers), Advanced Neuroimaging Techniques and Applications (2 papers) and Cardiovascular Health and Disease Prevention (1 paper). Daoying Geng is often cited by papers focused on Long-Term Effects of COVID-19 (3 papers), Advanced Neuroimaging Techniques and Applications (2 papers) and Cardiovascular Health and Disease Prevention (1 paper). Daoying Geng collaborates with scholars based in China and United Kingdom. Daoying Geng's co-authors include Yiping Lu, Bo Yin, Nan Mei, Dongdong Wang, Anling Xiao, Xuanxuan Li, Yajing Zhao, Pu‐Yeh Wu, Tianye Jia and Chu‐Chung Huang and has published in prestigious journals such as Chemical Engineering Journal, European Radiology and Computers in Biology and Medicine.

In The Last Decade

Daoying Geng

7 papers receiving 496 citations

Hit Papers

Cerebral Micro-Structural... 2020 2026 2022 2024 2020 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daoying Geng China 4 361 136 119 96 89 9 504
Yajing Zhao China 7 375 1.0× 147 1.1× 119 1.0× 100 1.0× 90 1.0× 15 493
Yiran Zhou China 9 223 0.6× 54 0.4× 80 0.7× 44 0.5× 64 0.7× 25 413
Anling Xiao China 5 370 1.0× 150 1.1× 119 1.0× 102 1.1× 90 1.0× 12 475
Nicola Trotta Belgium 13 231 0.6× 102 0.8× 56 0.5× 48 0.5× 80 0.9× 33 534
Tim Coolen Belgium 8 238 0.7× 106 0.8× 54 0.5× 48 0.5× 65 0.7× 16 358
Nina N. Kleineberg Germany 6 183 0.5× 99 0.7× 64 0.5× 25 0.3× 43 0.5× 15 308
Nivedha Kannapadi United States 7 431 1.2× 78 0.6× 202 1.7× 125 1.3× 83 0.9× 17 566
Johannes Thurow Germany 7 446 1.2× 92 0.7× 161 1.4× 180 1.9× 122 1.4× 13 538
Antonio Méndez-Guerrero Spain 9 760 2.1× 351 2.6× 120 1.0× 32 0.3× 123 1.4× 19 868
Umberto Pensato Italy 15 200 0.6× 90 0.7× 55 0.5× 21 0.2× 74 0.8× 61 589

Countries citing papers authored by Daoying Geng

Since Specialization
Citations

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

Fields of papers citing papers by Daoying Geng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daoying Geng

This figure shows the co-authorship network connecting the top 25 collaborators of Daoying Geng. A scholar is included among the top collaborators of Daoying Geng 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 Daoying Geng. Daoying Geng is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

9 of 9 papers shown
2.
Liu, Wei‐Min, et al.. (2025). Risk of acute cerebral infarction in patients with hypertension based on high-resolution MRI. Quantitative Imaging in Medicine and Surgery. 15(4). 3000–3010.
3.
Li, Zhiqiang, et al.. (2024). SRTRP-Net: A multi-task learning network for segmentation and prediction of stereotactic radiosurgery treatment response in brain metastases. Computers in Biology and Medicine. 175. 108503–108503. 3 indexed citations
4.
Li, Xuanxuan, Yiping Lu, Li Liu, et al.. (2023). Predicting peritumoral edema development after gamma knife radiosurgery of meningiomas using machine learning methods: a multicenter study. European Radiology. 33(12). 8912–8924. 6 indexed citations
5.
Zheng, Yingyan, Anling Xiao, Xiangrong Yu, et al.. (2020). Development and Validation of a Prognostic Nomogram Based on Clinical and CT Features for Adverse Outcome Prediction in Patients with COVID-19. Korean Journal of Radiology. 21(8). 1007–1007. 20 indexed citations
6.
Lu, Yiping, Xuanxuan Li, Daoying Geng, et al.. (2020). Letter response to the brain after COVID-19: Compensatory neurogenesis or persistent neuroinflammation?. EClinicalMedicine. 31. 100687–100687. 2 indexed citations
7.
Lu, Yiping, Xuanxuan Li, Daoying Geng, et al.. (2020). Cerebral Micro-Structural Changes in COVID-19 Patients – An MRI-based 3-month Follow-up Study. EClinicalMedicine. 25. 100484–100484. 417 indexed citations breakdown →
8.
She, Dejun, Shaojun Peng, Li Liu, et al.. (2020). Biomimic FeS2 nanodrug with hypothermal photothermal effect by clinical approved NIR-Ⅱ light for augmented chemodynamic therapy. Chemical Engineering Journal. 400. 125933–125933. 55 indexed citations
9.
Lu, Yiping, et al.. (2017). Axillary Apocrine Carcinoma with Bone Metastasis: First Report with Bone Scan Image. 2(1). 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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