Bin‐Jie Fu

442 total citations
36 papers, 224 citations indexed

About

Bin‐Jie Fu is a scholar working on Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging and Surgery. According to data from OpenAlex, Bin‐Jie Fu has authored 36 papers receiving a total of 224 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Pulmonary and Respiratory Medicine, 12 papers in Radiology, Nuclear Medicine and Imaging and 7 papers in Surgery. Recurrent topics in Bin‐Jie Fu's work include Lung Cancer Diagnosis and Treatment (23 papers), Medical Imaging and Pathology Studies (10 papers) and Radiomics and Machine Learning in Medical Imaging (8 papers). Bin‐Jie Fu is often cited by papers focused on Lung Cancer Diagnosis and Treatment (23 papers), Medical Imaging and Pathology Studies (10 papers) and Radiomics and Machine Learning in Medical Imaging (8 papers). Bin‐Jie Fu collaborates with scholars based in China, United Kingdom and Canada. Bin‐Jie Fu's co-authors include Zhi‐gang Chu, Fajin Lv, Yineng Zheng, Zijie Xu, Aiguo Zhou, Mingyue Wu, Fang Chen, Xiaochuan Zhang, Henry Sharp and John Rutka and has published in prestigious journals such as SHILAP Revista de lepidopterología, American Journal of Roentgenology and Medical Physics.

In The Last Decade

Bin‐Jie Fu

29 papers receiving 222 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Bin‐Jie Fu China 9 158 115 56 30 17 36 224
Giorgio De Conti Italy 6 33 0.2× 59 0.5× 13 0.2× 38 1.3× 9 0.5× 30 158
Agostina M. Fava United States 8 25 0.2× 79 0.7× 65 1.2× 83 2.8× 3 0.2× 24 289
Filippo Zilio Italy 8 27 0.2× 80 0.7× 10 0.2× 83 2.8× 4 0.2× 24 262
Algirdas Tamošiūnas Lithuania 8 23 0.1× 43 0.4× 20 0.4× 32 1.1× 3 0.2× 33 154
Hongyuan Liu China 4 229 1.4× 56 0.5× 10 0.2× 77 2.6× 8 275
Estefania De Gárate United Kingdom 9 20 0.1× 191 1.7× 15 0.3× 98 3.3× 4 0.2× 32 289
Michela Barini Italy 6 19 0.1× 53 0.5× 12 0.2× 23 0.8× 16 0.9× 13 145
Mara N.I. Szyrach Germany 8 128 0.8× 10 0.1× 18 0.3× 72 2.4× 3 0.2× 12 195
A. Calzado Spain 11 68 0.4× 256 2.2× 207 3.7× 13 0.4× 3 0.2× 28 306
Duarte Martins Portugal 9 48 0.3× 22 0.2× 9 0.2× 33 1.1× 19 1.1× 27 185

Countries citing papers authored by Bin‐Jie Fu

Since Specialization
Citations

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

Fields of papers citing papers by Bin‐Jie Fu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Bin‐Jie Fu. 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 Bin‐Jie Fu. The network helps show where Bin‐Jie Fu may publish in the future.

Co-authorship network of co-authors of Bin‐Jie Fu

This figure shows the co-authorship network connecting the top 25 collaborators of Bin‐Jie Fu. A scholar is included among the top collaborators of Bin‐Jie Fu 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 Bin‐Jie Fu. Bin‐Jie Fu 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.
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Zhang, Yi, et al.. (2024). CT Characteristics and Clinical Findings of Bronchopneumonia Caused by Pepper Aspiration. International Journal of General Medicine. Volume 17. 2757–2766.
4.
5.
Fu, Bin‐Jie, et al.. (2024). Progressive changes in non-neoplastic ground-glass nodules on follow-up computed tomography (CT). Quantitative Imaging in Medicine and Surgery. 14(12). 8467–8478.
6.
Gan, Hui, et al.. (2024). Artificial intelligence-measured nodule mass for determining the invasiveness of neoplastic ground glass nodules. Quantitative Imaging in Medicine and Surgery. 14(9). 6698–6710. 1 indexed citations
7.
Fu, Bin‐Jie, et al.. (2023). Proposal of Modified Lung-RADS in Assessing Pulmonary Nodules of Patients with Previous Malignancies: A Primary Study. Diagnostics. 13(13). 2210–2210. 1 indexed citations
8.
Lv, Fajin, et al.. (2023). Differentiation of pulmonary solid nodules attached to the pleura detected by thin-section CT. Insights into Imaging. 14(1). 146–146. 2 indexed citations
9.
Lv, Fajin, et al.. (2023). Quantitative evaluation of density variability in the lesion–lung boundary zone to differentiate pulmonary subsolid nodules. Quantitative Imaging in Medicine and Surgery. 13(2). 776–786. 1 indexed citations
10.
Fu, Bin‐Jie, et al.. (2023). The influence of different previous cancer histories on the diagnostic efficacy of Lung Imaging Reporting and Data System. Quantitative Imaging in Medicine and Surgery. 13(5). 2871–2880.
11.
Zhang, Xiaochuan, et al.. (2022). Clinical and Computed Tomography Characteristics for Early Diagnosis of Peripheral Small-cell Lung Cancer. SHILAP Revista de lepidopterología. 10 indexed citations
12.
Lv, Fajin, et al.. (2022). Clinical and Computed Tomography Characteristics of Solitary Pulmonary Nodules Caused by Fungi: A Comparative Study. Infection and Drug Resistance. Volume 15. 6019–6028. 2 indexed citations
13.
Ye, Min, et al.. (2022). Differential diagnosis of benign and malignant patchy ground-glass opacity by thin-section computed tomography. BMC Cancer. 22(1). 1206–1206. 5 indexed citations
14.
Ye, Xiaoping, et al.. (2021). Intravenous pyogenic granuloma in the internal jugular vein. Medicine. 100(6). e24570–e24570. 2 indexed citations
15.
Chen, Fang, et al.. (2021). Clinical and Computed Tomography (CT) Characteristics of Pulmonary Nodules Caused by Cryptococcal Infection. Infection and Drug Resistance. Volume 14. 4227–4235. 8 indexed citations
16.
Lv, Fajin, et al.. (2021). Features for Predicting Absorbable Pulmonary Solid Nodules as Depicted on Thin-Section Computed Tomography. Journal of Inflammation Research. Volume 14. 2933–2939. 7 indexed citations
17.
Lv, Fajin, et al.. (2021). Benign and malignant pulmonary part-solid nodules: differentiation via thin-section computed tomography. Quantitative Imaging in Medicine and Surgery. 12(1). 699–710. 17 indexed citations
18.
Liu, Xueyan, et al.. (2021). Completed absorption of coronavirus disease 2019 (COVID-19) pneumonia lesions: a preliminary study. International Journal of Medical Sciences. 18(11). 2321–2326. 1 indexed citations
19.
Fu, Bin‐Jie, et al.. (2020). <p>Follow-Up CT Results of COVID-19 Patients with Initial Negative Chest CT</p>. Infection and Drug Resistance. Volume 13. 2681–2687. 5 indexed citations
20.
Nixon, Iain J., et al.. (2005). A prospective study comparing conventional methods against a structured method of gaining patients’ informed consent for tonsillectomy. Clinical Otolaryngology. 30(5). 414–417. 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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