Ming Lu

4.9k total citations · 5 hit papers
60 papers, 2.4k citations indexed

About

Ming Lu is a scholar working on Oncology, Pulmonary and Respiratory Medicine and Physiology. According to data from OpenAlex, Ming Lu has authored 60 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Oncology, 18 papers in Pulmonary and Respiratory Medicine and 15 papers in Physiology. Recurrent topics in Ming Lu's work include Colorectal Cancer Screening and Detection (17 papers), Gastric Cancer Management and Outcomes (12 papers) and Alzheimer's disease research and treatments (12 papers). Ming Lu is often cited by papers focused on Colorectal Cancer Screening and Detection (17 papers), Gastric Cancer Management and Outcomes (12 papers) and Alzheimer's disease research and treatments (12 papers). Ming Lu collaborates with scholars based in China, United States and Sweden. Ming Lu's co-authors include Ying Yang, Yan Li, Lin Shen, Min Dai, Hongda Chen, Bin Lu, Yuhan Zhang, Jie Cai, Chenyu Luo and Na Li and has published in prestigious journals such as The Lancet, Journal of Clinical Oncology and Brain.

In The Last Decade

Ming Lu

56 papers receiving 2.4k citations

Hit Papers

5 papers align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Hepatogastroenterology

2011 973 citations Ming Lu et al. profile →
Advances in the epidemiology of pancreatic cancer: Trends, risk factors, screening, and prognosis

2021 260 citations Jie Cai, Hongda Chen et al. Cancer Letters profile →
Incidence, mortality, survival, risk factor and screening of colorectal cancer: A comparison among China, Europe, and northern America

2021 252 citations Na Li, Bin Lu et al. Cancer Letters profile →
Association of Donanemab Treatment With Exploratory Plasma Biomarkers in Early Symptomatic Alzheimer Disease

2022 138 citations Michael J. Pontecorvo, Ming Lu et al. JAMA Neurology profile →
Amyloid-Related Imaging Abnormalities With Donanemab in Early Symptomatic Alzheimer Disease

2025 29 citations Jennifer A. Zimmer, Paul Ardayfio et al. JAMA Neurology profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ming Lu China	16	780	610	514	499	424	60	2.4k
Jan DʼHaese Germany	32	1.3k 1.7×	1.1k 1.9×	929 1.8×	1.0k 2.0×	243 0.6×	111	3.8k
Clara Chen United States	24	832 1.1×	402 0.7×	604 1.2×	401 0.8×	264 0.6×	101	2.6k
Bei Zhang China	26	942 1.2×	357 0.6×	682 1.3×	464 0.9×	87 0.2×	191	2.4k
Shiying Yu China	31	1.3k 1.7×	459 0.8×	1.5k 2.9×	926 1.9×	496 1.2×	141	3.7k
Shigemi Matsumoto Japan	26	1.6k 2.1×	557 0.9×	866 1.7×	636 1.3×	233 0.5×	136	3.2k
Mi Jung Kwon South Korea	22	601 0.8×	407 0.7×	590 1.1×	463 0.9×	116 0.3×	202	2.0k
Ingiäld Hafström Sweden	39	289 0.4×	467 0.8×	846 1.6×	191 0.4×	510 1.2×	111	4.8k
Naoki Nagata Japan	28	1.0k 1.3×	507 0.8×	1.2k 2.4×	439 0.9×	115 0.3×	136	3.0k
Thomas A. Colacchio United States	27	1.1k 1.4×	943 1.5×	296 0.6×	561 1.1×	165 0.4×	65	2.6k
Zheng Jiang China	27	705 0.9×	412 0.7×	738 1.4×	385 0.8×	161 0.4×	146	2.3k

Countries citing papers authored by Ming Lu

Since Specialization

Citations

This map shows the geographic impact of Ming 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 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 Lu more than expected).

Fields of papers citing papers by Ming Lu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ming Lu

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Liu, Xiaoyan, et al.. (2025). The association between reproductive factors and frailty risk: a population-based analysis from the UK biobank. BMC Public Health. 25(1). 762–762. 2 indexed citations

Lu, Ming, Emily C. Collins, Sergey Shcherbinin, et al.. (2025). Posttreatment Amyloid Levels and Clinical Outcomes Following Donanemab for Early Symptomatic Alzheimer Disease. JAMA Neurology. 82(12). 1251–1251. 2 indexed citations

Lu, Ming, Bin Lu, & Le Wang. (2024). Temporal Decomposition Analysis of Noncommunicable Disease Burden: The Interplay of Population Aging, Population Growth, and Low Physical Activity, 2010–2019. Journal of Physical Activity and Health. 22(3). 307–316. 1 indexed citations

Li, Mengling, et al.. (2024). Classification of molecular subtypes for colorectal cancer and development of a prognostic model based on necroptosis-related genes. Heliyon. 10(5). e26781–e26781. 1 indexed citations

Mintun, Mark A., Craig Ritchie, Paul R. Solomon, et al.. (2023). Donanemab in Early Symptomatic Alzheimer’s Disease: Efficacy and Safety in TRAILBLAZER‐ALZ 2, a Phase 3 Randomized Clinical Trial. Alzheimer s & Dementia. 19(S24). 6 indexed citations

Wang, Jian, et al.. (2023). Bayesian network analysis of BIN1 risk allele and other risk factors and biomarkers of Alzheimer’s disease. Alzheimer s & Dementia. 19(S12). 1 indexed citations

Wang, Hong, Stephen Salloway, Michelle Papka, et al.. (2023). TRAILBLAZER‐ALZ 4: Directly comparing donanemab to aducanumab on amyloid lowering in early, symptomatic Alzheimer’s disease ‐ Results from 12‐months. Alzheimer s & Dementia. 19(S24). e082529–e082529. 5 indexed citations

Zhou, Jiao, Sheng Wei, Xiumei Guo, et al.. (2023). Correlation between preoperative peripheral blood NLR, PLR, LMR and prognosis of patients with head and neck squamous cell carcinoma. BMC Cancer. 23(1). 1247–1247. 9 indexed citations

Wang, Chenyi, Yao Lyu, Ming Lu, et al.. (2023). A novel inflammation-related prognostic model for predicting the overall survival of primary central nervous system lymphoma: A real-world data analysis. Frontiers in Oncology. 13. 3 indexed citations

10.

Shcherbinin, Sergey, Amanda Sheffield Morris, Ixavier A. Higgins, et al.. (2023). Tau as a diagnostic instrument in clinical trials to predict amyloid in Alzheimer's disease. Alzheimer s & Dementia Translational Research & Clinical Interventions. 9(3). e12415–e12415. 10 indexed citations

11.

Wang, Le, Hongda Chen, Ming Lu, et al.. (2022). One-sample quantitative and two-sample qualitative faecal immunochemical tests for colorectal cancer screening: a cross-sectional study in China. BMJ Open. 12(5). e059754–e059754. 6 indexed citations

12.

Lu, Ming, et al.. (2022). Establishment and validation of a postoperative predictive model for patients with colorectal mucinous adenocarcinoma. World Journal of Surgical Oncology. 20(1). 330–330. 4 indexed citations

13.

Lo, Albert, Cynthia Evans, Michele Mancini, et al.. (2021). Phase II (NAVIGATE-AD study) Results of LY3202626 Effects on Patients with Mild Alzheimer’s Disease Dementia. Journal of Alzheimer s Disease Reports. 5(1). 321–336. 22 indexed citations

14.

Li, Na, Bin Lu, Chenyu Luo, et al.. (2021). Incidence, mortality, survival, risk factor and screening of colorectal cancer: A comparison among China, Europe, and northern America. Cancer Letters. 522. 255–268. 252 indexed citations breakdown →

15.

Chen, Hongda, Le Wang, Ming Lu, et al.. (2021). Comparative yield and efficiency of strategies based on risk assessment and fecal immunochemical test in colorectal cancer screening: A cross-sectional population-based analysis. Chinese Journal of Cancer Research. 33(4). 512–521. 9 indexed citations

16.

Chen, Hongda, Ming Lu, Yuhan Zhang, & Min Dai. (2021). Divergent detection rates of fecal immunochemical test and questionnaire-based risk assessment for detecting proximal and distal advanced colorectal adenomas. Chinese Medical Journal. 134(5). 605–607. 2 indexed citations

17.

Lu, Ming, et al.. (2017). Epidemiologic features and management of elbow dislocation with associated fracture in pediatric population. Medicine. 96(48). e8595–e8595. 5 indexed citations

18.

Fan, Dongsheng, et al.. (2009). [Basic and clinical researches on amyotrophic lateral sclerosis/motor neuron disease].. PubMed. 41(3). 279–81. 1 indexed citations

19.

Zhu, Yaowei, Chuanpu Hu, Ming Lu, et al.. (2009). Population Pharmacokinetic Modeling of Ustekinumab, a Human Monoclonal Antibody Targeting IL‐12/23p40, in Patients With Moderate to Severe Plaque Psoriasis. The Journal of Clinical Pharmacology. 49(2). 162–175. 135 indexed citations

20.

Zhou, Honghui, Chuanpu Hu, Yaowei Zhu, et al.. (2009). Population‐Based Exposure‐Efficacy Modeling of Ustekinumab in Patients With Moderate to Severe Plaque Psoriasis. The Journal of Clinical Pharmacology. 50(3). 257–267. 50 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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