Mingming Lu

679 total citations
34 papers, 216 citations indexed

About

Mingming Lu is a scholar working on Pulmonary and Respiratory Medicine, Rheumatology and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Mingming Lu has authored 34 papers receiving a total of 216 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Pulmonary and Respiratory Medicine, 12 papers in Rheumatology and 10 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Mingming Lu's work include Cerebrovascular and Carotid Artery Diseases (16 papers), Moyamoya disease diagnosis and treatment (12 papers) and Intracranial Aneurysms: Treatment and Complications (9 papers). Mingming Lu is often cited by papers focused on Cerebrovascular and Carotid Artery Diseases (16 papers), Moyamoya disease diagnosis and treatment (12 papers) and Intracranial Aneurysms: Treatment and Complications (9 papers). Mingming Lu collaborates with scholars based in China, United States and India. Mingming Lu's co-authors include Jianming Cai, Xihai Zhao, Peng Peng, Huiyu Qiao, Yuanyuan Cui, Dongye Li, Yao He, Dongqing Liu, Fugeng Sheng and Cong Han and has published in prestigious journals such as Journal of Clinical Investigation, Stroke and Journal of Neurology Neurosurgery & Psychiatry.

In The Last Decade

Mingming Lu

29 papers receiving 214 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mingming Lu China 8 148 92 69 60 54 34 216
Kaijiang Kang China 9 74 0.5× 29 0.3× 85 1.2× 64 1.1× 136 2.5× 34 219
Joel Cohn United States 7 94 0.6× 72 0.8× 36 0.5× 18 0.3× 59 1.1× 11 191
L Irace Italy 10 282 1.9× 202 2.2× 127 1.8× 26 0.4× 78 1.4× 50 392
Daniel Guisado‐Alonso Spain 8 67 0.5× 48 0.5× 73 1.1× 16 0.3× 92 1.7× 30 182
Mikel Terceño Spain 10 84 0.6× 26 0.3× 151 2.2× 15 0.3× 124 2.3× 28 270
Ka Lung Chan Hong Kong 7 165 1.1× 47 0.5× 171 2.5× 8 0.1× 77 1.4× 9 222
Neil Rane United Kingdom 9 126 0.9× 44 0.5× 100 1.4× 17 0.3× 94 1.7× 19 234
Marco Papa Italy 11 112 0.8× 115 1.3× 94 1.4× 11 0.2× 17 0.3× 29 297
T.G. Brott United States 5 166 1.1× 97 1.1× 182 2.6× 15 0.3× 80 1.5× 6 296
Kimitoshi Sato Japan 7 32 0.2× 20 0.2× 60 0.9× 41 0.7× 128 2.4× 32 181

Countries citing papers authored by Mingming Lu

Since Specialization
Citations

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

Fields of papers citing papers by Mingming Lu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mingming Lu

This figure shows the co-authorship network connecting the top 25 collaborators of Mingming Lu. A scholar is included among the top collaborators of Mingming Lu 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 Mingming Lu. Mingming Lu 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.
Lu, Mingming, et al.. (2025). Analysis of Risk Factors Associated with Organic Erectile Dysfunction in Patients with Type 2 Diabetes Mellitus and Erectile Dysfunction. Discovery Medicine. 37(192). 141–141. 2 indexed citations
2.
Lu, Mingming, Zi‐Ai Zhao, Shu Wang, et al.. (2025). Global Hotspots and Research Frontiers of Moyamoya Disease and Radiological Features: A Bibliometric Analysis. World Neurosurgery. 197. 123817–123817.
3.
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Lu, Mingming, Hongtao Zhang, Shitong Liu, et al.. (2025). Effects of antiplatelet therapy on reducing stroke risk in patients with moyamoya disease: the role of postcontrast MR vessel wall imaging. European Radiology. 35(10). 5911–5921.
6.
Han, Cong, Mingming Lu, Yue Wang, et al.. (2024). High-resolution MRI vessel wall enhancement in moyamoya disease: risk factors and clinical outcomes. European Radiology. 34(8). 5179–5189. 4 indexed citations
7.
Wang, Minjie, Hui Wang, Mingming Lu, et al.. (2024). Risk Factors for Massive Cerebral Infarction in Pediatric Patients With Moyamoya Disease. Pediatric Neurology. 153. 159–165. 2 indexed citations
8.
Lu, Mingming, Yuan Liu, Peng Peng, et al.. (2024). Deep learning model for automated diagnosis of moyamoya disease based on magnetic resonance angiography. EClinicalMedicine. 77. 102888–102888. 3 indexed citations
9.
Lu, Mingming, et al.. (2024). Optimization of Hydropower Unit Startup Process Based on the Improved Multi-Objective Particle Swarm Optimization Algorithm. Energies. 17(17). 4473–4473. 3 indexed citations
10.
Lu, Mingming, Dongqing Liu, Xu Liu, et al.. (2023). Predictors of Stroke Outcomes in Conservatively Treated Patients With Moyamoya Disease: A Follow‐up MRI Study. Journal of Magnetic Resonance Imaging. 59(4). 1456–1463. 3 indexed citations
11.
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Liu, Shaohua, Zhiqiang Li, Shengshu Wang, et al.. (2023). Association between different adiposity measures and all-cause mortality risk among centenarians: A prospective cohort study. Clinical Nutrition. 42(7). 1219–1226. 1 indexed citations
13.
Lu, Mingming, Hongtao Zhang, Dongqing Liu, et al.. (2023). Long-term outcomes of moyamoya disease versus atherosclerosis-associated moyamoya vasculopathy using high-resolution MR vessel wall imaging. Journal of Neurology Neurosurgery & Psychiatry. 94(7). 567–574. 11 indexed citations
14.
Lu, Mingming, et al.. (2022). The Value of Preoperative Phase-Contrast MRI in Predicting the Clinical Outcome of Moyamoya Disease after Encephalo-Duro-Arterial Synangiosis Surgery. American Journal of Neuroradiology. 43(11). 1582–1588. 1 indexed citations
15.
Lu, Mingming, Hongtao Zhang, Dongqing Liu, et al.. (2022). Vessel wall enhancement as a predictor of arterial stenosis progression and poor outcomes in moyamoya disease. European Radiology. 33(4). 2489–2499. 13 indexed citations
16.
Lu, Mingming, Peng Peng, Shaohua Liu, et al.. (2022). Predictors of Progression in Intraplaque Hemorrhage Volume in Patients With Carotid Atherosclerosis: A Serial Magnetic Resonance Imaging Study. Frontiers in Neurology. 13. 815150–815150. 2 indexed citations
17.
Zhu, Li‐Na, Mingming Lu, Xihai Zhao, et al.. (2021). Comparison of Carotid Plaque Characteristics Between Men and Women Using Magnetic Resonance Vessel Wall Imaging: A Chinese Atherosclerosis Risk Evaluation Study. Journal of Magnetic Resonance Imaging. 54(2). 646–654. 6 indexed citations
18.
Dong, Jinghui, Mingming Lu, Fugeng Sheng, et al.. (2021). Severe Thrombocytopenia and Disseminated Intravascular Coagulation in a Cirrhosis Patient After Intravenous Injection of Gadoxetic Acid. Journal of Magnetic Resonance Imaging. 55(6). 1904–1906. 1 indexed citations
19.
Lu, Mingming, Peng Peng, Huiyu Qiao, et al.. (2019). Association between age and progression of carotid artery atherosclerosis: a serial high resolution magnetic resonance imaging study. International journal of cardiac imaging. 35(7). 1287–1295. 7 indexed citations
20.
Lu, Mingming, et al.. (2019). Segment-specific progression of carotid artery atherosclerosis: a magnetic resonance vessel wall imaging study. Neuroradiology. 62(2). 211–220. 4 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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