Changfa Qu

512 total citations
8 papers, 417 citations indexed

About

Changfa Qu is a scholar working on Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging and Oncology. According to data from OpenAlex, Changfa Qu has authored 8 papers receiving a total of 417 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Pulmonary and Respiratory Medicine, 4 papers in Radiology, Nuclear Medicine and Imaging and 3 papers in Oncology. Recurrent topics in Changfa Qu's work include Lung Cancer Diagnosis and Treatment (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers) and RNA modifications and cancer (2 papers). Changfa Qu is often cited by papers focused on Lung Cancer Diagnosis and Treatment (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers) and RNA modifications and cancer (2 papers). Changfa Qu collaborates with scholars based in China, Australia and Macao. Changfa Qu's co-authors include David Goldstein, Phoebe A. Phillips, Alain Vonlaufen, Romano C. Pirola, Zhihong Xu, Nicole Parker, Minoti V. Apte, Swapna Joshi, Jeremy S. Wilson and Barry Allen and has published in prestigious journals such as Journal of Clinical Oncology, Cancer Research and Cancer Letters.

In The Last Decade

Changfa Qu

8 papers receiving 414 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Changfa Qu China	4	323	118	115	112	56	8	417
Müge Sarper United Kingdom	6	290 0.9×	104 0.9×	93 0.8×	161 1.4×	89 1.6×	7	481
David J. Bajor United States	6	418 1.3×	140 1.2×	54 0.5×	131 1.2×	106 1.9×	15	491
Mary Topalovski United States	5	194 0.6×	122 1.0×	47 0.4×	117 1.0×	82 1.5×	5	341
Zhongxu Yuan China	9	342 1.1×	263 2.2×	104 0.9×	194 1.7×	61 1.1×	15	492
Paul-Yang Lin Taiwan	7	227 0.7×	159 1.3×	99 0.9×	124 1.1×	61 1.1×	8	404
Xingyuan Xu China	9	184 0.6×	297 2.5×	111 1.0×	143 1.3×	112 2.0×	9	519
Anke Van den broeck Belgium	6	285 0.9×	53 0.4×	63 0.5×	233 2.1×	128 2.3×	9	433
Anne Steins Netherlands	10	248 0.8×	50 0.4×	91 0.8×	113 1.0×	96 1.7×	16	395
Hidehiko Takigawa Japan	12	151 0.5×	75 0.6×	138 1.2×	115 1.0×	68 1.2×	55	437
Maria M. Steele United States	12	319 1.0×	168 1.4×	57 0.5×	194 1.7×	66 1.2×	20	494

Countries citing papers authored by Changfa Qu

Since Specialization

Citations

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

Fields of papers citing papers by Changfa Qu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Changfa Qu

This figure shows the co-authorship network connecting the top 25 collaborators of Changfa Qu. A scholar is included among the top collaborators of Changfa Qu 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 Changfa Qu. Changfa Qu 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:

8 of 8 papers shown

1.

Wang, Lin, Jing Zhang, Sihua Wang, et al.. (2025). Ensartinib as postoperative adjuvant therapy in patients with ALK-positive non-small cell lung cancer (NSCLC): A registered, retrospective, real-world study.. Journal of Clinical Oncology. 43(16_suppl). 8024–8024. 2 indexed citations

2.

Bu, Jianlong, et al.. (2024). Investigation of mediastinal lymph node dissection in clinical stage IA pure-solid non-small cell lung cancer patients. Journal of Cardiothoracic Surgery. 19(1). 357–357. 1 indexed citations

3.

Liu, Mengfeng, et al.. (2023). Predictive Value of Gene Databases in Discovering New Biomarkers and New Therapeutic Targets in Lung Cancer. Medicina. 59(3). 547–547. 2 indexed citations

4.

Liu, Mengfeng, et al.. (2022). Characterization of lung adenocarcinoma based on immunophenotyping and constructing an immune scoring model to predict prognosis. Frontiers in Pharmacology. 13. 1081244–1081244. 2 indexed citations

5.

Zhu, Kaibin, Changjun He, Yaoguo Lang, et al.. (2020). Prediction of Pleural Invasion in Challenging Non-Small-Cell Lung Cancer Patients Using Serum and Imaging Markers. Disease Markers. 2020. 1–6. 5 indexed citations

6.

Li, Xia, Xuan Hou, Yujun Wang, et al.. (2016). Preparation and evaluation of 131I-quercetin as a novel radiotherapy agent against dedifferentiated thyroid cancer. Journal of Radioanalytical and Nuclear Chemistry. 311(3). 1697–1708. 8 indexed citations

7.

Vonlaufen, Alain, Swapna Joshi, Changfa Qu, et al.. (2008). Pancreatic Stellate Cells: Partners in Crime with Pancreatic Cancer Cells. Cancer Research. 68(7). 2085–2093. 390 indexed citations

8.

Zhang, David Y., Yong Li, Syed Rizvi, et al.. (2004). Cytotoxicity of breast cancer cells overexpressing HER2/neu by 213Bi-Herceptin radioimmunoconjugate. Cancer Letters. 218(2). 181–190. 7 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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