Lianfang Du

1.0k total citations
65 papers, 762 citations indexed

About

Lianfang Du is a scholar working on Cardiology and Cardiovascular Medicine, Radiology, Nuclear Medicine and Imaging and Surgery. According to data from OpenAlex, Lianfang Du has authored 65 papers receiving a total of 762 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Cardiology and Cardiovascular Medicine, 19 papers in Radiology, Nuclear Medicine and Imaging and 17 papers in Surgery. Recurrent topics in Lianfang Du's work include Cardiovascular Health and Disease Prevention (17 papers), Ultrasound and Hyperthermia Applications (11 papers) and Ultrasound Imaging and Elastography (10 papers). Lianfang Du is often cited by papers focused on Cardiovascular Health and Disease Prevention (17 papers), Ultrasound and Hyperthermia Applications (11 papers) and Ultrasound Imaging and Elastography (10 papers). Lianfang Du collaborates with scholars based in China, United Kingdom and Taiwan. Lianfang Du's co-authors include Jiying Gu, Min Bai, Zhaojun Li, Fan Li, Fan Li, Feng Gao, Xiao-Hui Qiao, Jiajie Zhang, Lizhou Lin and Lingxi Xing and has published in prestigious journals such as Scientific Reports, BioMed Research International and Oncotarget.

In The Last Decade

Lianfang Du

60 papers receiving 753 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Lianfang Du China 16 317 233 170 155 146 65 762
Priscilla Machado United States 17 447 1.4× 441 1.9× 249 1.5× 47 0.3× 125 0.9× 83 966
J.M. Corréas France 16 288 0.9× 210 0.9× 261 1.5× 23 0.1× 252 1.7× 53 838
Daniele Fresilli Italy 14 211 0.7× 81 0.3× 185 1.1× 45 0.3× 86 0.6× 22 465
Guenther Schneider Germany 18 337 1.1× 61 0.3× 372 2.2× 108 0.7× 235 1.6× 47 1.0k
Nicola Maggialetti Italy 17 324 1.0× 57 0.2× 232 1.4× 35 0.2× 139 1.0× 70 773
Kumiko Naito Japan 8 270 0.9× 117 0.5× 219 1.3× 13 0.1× 43 0.3× 18 599
Emanuele David Italy 11 166 0.5× 68 0.3× 125 0.7× 25 0.2× 75 0.5× 48 435
Andrea Murray United Kingdom 22 199 0.6× 98 0.4× 287 1.7× 26 0.2× 39 0.3× 78 1.1k
Bernhard Kraemer Germany 20 168 0.5× 85 0.4× 524 3.1× 40 0.3× 102 0.7× 79 1.2k
Pierpaolo Palumbo Italy 20 409 1.3× 160 0.7× 294 1.7× 67 0.4× 274 1.9× 87 1.1k

Countries citing papers authored by Lianfang Du

Since Specialization
Citations

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

Fields of papers citing papers by Lianfang Du

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lianfang Du

This figure shows the co-authorship network connecting the top 25 collaborators of Lianfang Du. A scholar is included among the top collaborators of Lianfang Du 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 Lianfang Du. Lianfang Du 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.
Du, Lianfang, et al.. (2025). Deep Learning for Classification of Solid Renal Parenchymal Tumors Using Contrast-Enhanced Ultrasound. Journal of Imaging Informatics in Medicine. 39(1). 277–285.
2.
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Fan, Chengjuan, Che‐Ming Teng, Xiaowei Song, et al.. (2024). Efficacy and safety of intrathecal pemetrexed for TKI-failed leptomeningeal metastases from EGFR+ NSCLC: an expanded, single-arm, phase II clinical trial. ESMO Open. 9(4). 102384–102384. 16 indexed citations
5.
Zhao, Lei, Ruitao Wang, Lianfang Du, et al.. (2024). Predictive value of contrast-enhanced ultrasonography and ultrasound elastography for management of BI-RADS category 4 nonpalpable breast masses. European Journal of Radiology. 173. 111391–111391. 1 indexed citations
6.
Chen, Qingqing, et al.. (2023). Arterial Stiffness, Body Mass Index and Cardiovascular Disease Risk in Chinese Females at Various Ages. Reviews in Cardiovascular Medicine. 24(5). 144–144. 3 indexed citations
7.
Wang, Yixuan, et al.. (2023). Sequence and directivity in cardiac muscle injury of COVID-19 patients: an observational study. Frontiers in Cardiovascular Medicine. 10. 1260971–1260971. 1 indexed citations
8.
Chen, Qingqing, et al.. (2023). Increased arterial pressure volume index and cardiovascular risk score in China. BMC Cardiovascular Disorders. 23(1). 22–22. 7 indexed citations
9.
Li, Fan, et al.. (2019). Diagnostic Performance of Ultrasound Shear Wave Elastography in Solid Small (≤4 cm) Renal Parenchymal Masses. Ultrasound in Medicine & Biology. 45(9). 2328–2337. 11 indexed citations
10.
Zheng, Fang, et al.. (2019). Role of Ultrasound in the Detection of Rotator-Cuff Syndrome: An Observational Study. Medical Science Monitor. 25. 5856–5863. 18 indexed citations
11.
Zheng, Fang, et al.. (2019). Transvaginal three-dimensional ultrasound combined with HD flow model for uterus scar diverticulum. Journal of Infection and Public Health. 13(12). 2014–2019. 3 indexed citations
12.
Bai, Yun, et al.. (2018). Gender difference in ventricular-vascular coupling in response to exercises in medical graduate students. 1(1). 5–13. 1 indexed citations
13.
Hang, Jing, et al.. (2017). Investigation of the maximum Young's modulus of thyroid nodules using two-dimensional shear wave elastography in thyroid nodules. Biomedical Research-tokyo. 28(8). 3537–3544. 2 indexed citations
14.
Li, Fan, Feng Gao, Yang Liu, et al.. (2016). The Value of the Model and Quantitative Parameters of Contrast-Enhanced Ultrasound in Judging the Severity of SHPT. BioMed Research International. 2016. 1–5. 4 indexed citations
15.
Liu, Yang, Fan Li, Feng Gao, et al.. (2016). Role of microenvironmental periostin in pancreatic cancer progression. Oncotarget. 8(52). 89552–89565. 32 indexed citations
16.
Xu, Changsong, et al.. (2016). Correlation between blood circulation grading and angiogenesis using ultrasonic contrast of rabbit VX2 hepatic carcinoma. Asian Pacific Journal of Tropical Medicine. 9(2). 153–157. 1 indexed citations
17.
Li, Zhaojun, et al.. (2015). Identi cation of carotid artery dissection by contrast enhanced ultrasonography. A case report. Medical Ultrasonography. 17(4). 564–5. 7 indexed citations
18.
Du, Lianfang, et al.. (2012). Recent advances of ultrasonic diagnosis in renal cell carcinoma. Zhonghua chaosheng yingxiangxue zazhi. 21(6). 540–542. 1 indexed citations
19.
Gu, Jiying, Lianfang Du, Min Bai, et al.. (2012). Preliminary Study on the Diagnostic Value of Acoustic Radiation Force Impulse Technology for Differentiating Between Benign and Malignant Thyroid Nodules. Journal of Ultrasound in Medicine. 31(5). 763–771. 72 indexed citations
20.
Zheng, Xiao-Zhi, Lianfang Du, & Huiping Wang. (2010). Evaluation of left ventricular hypertrophy in hypertensive patients with echocardiographic myocardial videodensitometry normalized by displacement. Bosnian Journal of Basic Medical Sciences. 10(4). 292–296. 3 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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