Ming-Jen Lu

1.2k total citations
23 papers, 920 citations indexed

About

Ming-Jen Lu is a scholar working on Cardiology and Cardiovascular Medicine, Surgery and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Ming-Jen Lu has authored 23 papers receiving a total of 920 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Cardiology and Cardiovascular Medicine, 10 papers in Surgery and 8 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Ming-Jen Lu's work include Atrial Fibrillation Management and Outcomes (5 papers), Cardiovascular Function and Risk Factors (4 papers) and Cardiac Imaging and Diagnostics (3 papers). Ming-Jen Lu is often cited by papers focused on Atrial Fibrillation Management and Outcomes (5 papers), Cardiovascular Function and Risk Factors (4 papers) and Cardiac Imaging and Diagnostics (3 papers). Ming-Jen Lu collaborates with scholars based in Taiwan and United States. Ming-Jen Lu's co-authors include Chi‐Ren Hung, Hsiang‐Yu Yuan, Ying‐Fu Chen, Chun-Yu Wei, Chien-Hsiun Chen, Min‐Ji Charng, Jin‐Jer Chen, Jer‐Yuarn Wu, Yuan-Tsong Chen and Kou‐Gi Shyu and has published in prestigious journals such as Human Molecular Genetics, Life Sciences and Journal of Thoracic and Cardiovascular Surgery.

In The Last Decade

Ming-Jen Lu

20 papers receiving 890 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ming-Jen Lu Taiwan 13 403 318 179 179 129 23 920
Jessie N. Lindsley United States 19 213 0.5× 85 0.3× 401 2.2× 177 1.0× 138 1.1× 30 1.4k
Lisa Kurland Sweden 15 392 1.0× 207 0.7× 191 1.1× 389 2.2× 48 0.4× 20 705
Ketul R. Chaudhary Canada 17 258 0.6× 112 0.4× 176 1.0× 230 1.3× 414 3.2× 21 835
Arlene B. Chapman United States 18 448 1.1× 194 0.6× 337 1.9× 523 2.9× 52 0.4× 42 1.2k
Rania Nasrallah Canada 17 192 0.5× 59 0.2× 402 2.2× 234 1.3× 194 1.5× 34 1.2k
Fabiana Filigheddu Italy 14 353 0.9× 81 0.3× 198 1.1× 432 2.4× 30 0.2× 25 787
Ugo Cavallari Italy 16 428 1.1× 39 0.1× 191 1.1× 189 1.1× 115 0.9× 30 967
Ling Tu China 19 121 0.3× 77 0.2× 318 1.8× 275 1.5× 368 2.9× 59 1.1k
Noriko Aoi Japan 16 165 0.4× 105 0.3× 187 1.0× 247 1.4× 163 1.3× 39 628
Kengo Azushima Japan 21 503 1.2× 52 0.2× 390 2.2× 492 2.7× 29 0.2× 94 1.5k

Countries citing papers authored by Ming-Jen Lu

Since Specialization
Citations

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

Fields of papers citing papers by Ming-Jen Lu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ming-Jen Lu

This figure shows the co-authorship network connecting the top 25 collaborators of Ming-Jen Lu. A scholar is included among the top collaborators of Ming-Jen 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 Ming-Jen Lu. Ming-Jen 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, Ming-Jen, et al.. (2021). Use of modified-NUTRIC score to assess nutritional risk in surgical intensive care unit. Journal of the Chinese Medical Association. 84(9). 860–864. 8 indexed citations
2.
Lu, Ming-Jen, et al.. (2020). A Simple and Effective Method to Treat Perigraft Seroma: A Case Report. Zenodo (CERN European Organization for Nuclear Research). 5(2).
3.
4.
Lo, Huey‐Ming, et al.. (2016). Atorvastatin alleviates cardiomyocyte apoptosis by suppressing TRB3 induced by acute myocardial infarction and hypoxia. Journal of the Formosan Medical Association. 116(5). 388–397. 15 indexed citations
5.
Chua, Su-Kiat, Kou‐Gi Shyu, Ming-Jen Lu, et al.. (2015). Renal dysfunction and the risk of postoperative atrial fibrillation after cardiac surgery: role beyond the CHA2DS2-VASc score. EP Europace. 17(9). 1363–1370. 26 indexed citations
6.
7.
Lu, Ming-Jen, et al.. (2015). Initial Experience of Modified Four-Branched Graft Technique and Antegrade TEVAR in Acute Type A Aortic Dissection. Annals of Thoracic and Cardiovascular Surgery. 21(5). 481–486. 3 indexed citations
8.
Lu, Ming-Jen, Yih‐Sharng Chen, Ho‐Shiang Huang, & Ming‐Chieh Ma. (2014). Hypoxic preconditioning protects rat hearts against ischemia–reperfusion injury via the arachidonate12-lipoxygenase/transient receptor potential vanilloid 1 pathway. Basic Research in Cardiology. 109(4). 414–414. 43 indexed citations
9.
Chua, Su-Kiat, Kou‐Gi Shyu, Ming-Jen Lu, et al.. (2013). Clinical utility of CHADS2 and CHA2DS2-VASc scoring systems for predicting postoperative atrial fibrillation after cardiac surgery. Journal of Thoracic and Cardiovascular Surgery. 146(4). 919–926.e1. 87 indexed citations
10.
Chua, Su-Kiat, Kou‐Gi Shyu, Ming-Jen Lu, et al.. (2013). Association Between Renal Function, Diastolic Dysfunction, and Postoperative Atrial Fibrillation Following Cardiac Surgery. Circulation Journal. 77(9). 2303–2310. 19 indexed citations
11.
Lu, Ming-Jen, Yih‐Sharng Chen, Ho‐Shiang Huang, & Ming‐Chieh Ma. (2012). Erythropoietin alleviates post-ischemic injury of rat hearts by attenuating nitrosative stress. Life Sciences. 90(19-20). 776–784. 22 indexed citations
12.
Lu, Ming-Jen, et al.. (2012). Endovascular Stent Graft Repair for a Salmonella-Infected Aneurysm of Thoracic Aorta. Annals of Vascular Surgery. 26(5). 731.e5–731.e8. 6 indexed citations
13.
Hu, Wei‐Syun, et al.. (2010). Intracardiac Extension of a Pulmonary Pleomorphic Carcinoma. Zhōnghuá mínguó xīnzàngxué huì zázhì. 26(1). 41–43.
14.
Chen, Yih‐Sharng, Ming-Jen Lu, Ho‐Shiang Huang, & Ming‐Chieh Ma. (2010). Mechanosensitive transient receptor potential vanilloid type 1 channels contribute to vascular remodeling of rat fistula veins. Journal of Vascular Surgery. 52(5). 1310–1320. 27 indexed citations
15.
Liou, Jer-Young, et al.. (2006). Pericardial Fluid and Serum Levels of Vascular Endothelial Growth Factor and Endostatin in Patients With or Without Coronary Artery Disease. Journal of the Formosan Medical Association. 105(5). 377–383. 16 indexed citations
16.
Shyu, Kou‐Gi, et al.. (2006). Myostatin expression in ventricular myocardium in a rat model of volume‐overload heart failure. European Journal of Clinical Investigation. 36(10). 713–719. 81 indexed citations
17.
Chao, Hung‐Hsing, Ming-Jen Lu, & Chi‐Ren Hung. (2005). Spontaneous Rupture of Left Ventricular True Aneurysm. The Annals of Thoracic Surgery. 80(3). 1106–1108. 2 indexed citations
18.
Lu, Ming-Jen, et al.. (2003). Spontaneous cardiac rupture. The Annals of Thoracic Surgery. 76(3). 921–923. 3 indexed citations
19.
Lee, Shih-Huang, Che-Ming Chang, Ming-Jen Lu, et al.. (2000). Intravenous amiodarone for prevention of atrial fibrillation after coronary artery bypass grafting. The Annals of Thoracic Surgery. 70(1). 157–161. 84 indexed citations
20.
Chang, Che-Ming, Shih-Huang Lee, Ming-Jen Lu, et al.. (1999). The role of P wave in prediction of atrial fibrillation after coronary artery surgery. International Journal of Cardiology. 68(3). 303–308. 52 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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