Bing Fan

2.4k total citations · 1 hit paper
72 papers, 1.5k citations indexed

About

Bing Fan is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Biomedical Engineering. According to data from OpenAlex, Bing Fan has authored 72 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Radiology, Nuclear Medicine and Imaging, 21 papers in Pulmonary and Respiratory Medicine and 15 papers in Biomedical Engineering. Recurrent topics in Bing Fan's work include Radiomics and Machine Learning in Medical Imaging (23 papers), Advanced X-ray and CT Imaging (9 papers) and COVID-19 diagnosis using AI (8 papers). Bing Fan is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (23 papers), Advanced X-ray and CT Imaging (9 papers) and COVID-19 diagnosis using AI (8 papers). Bing Fan collaborates with scholars based in China, United States and Yemen. Bing Fan's co-authors include Bingliang Zeng, Zicong Li, Chuanhong Wang, Qinglin Shen, Xiaofen Li, Honglu Li, Pinggui Lei, Jiaqi Liu, Peng Yu and Xiaoqi Lin and has published in prestigious journals such as Scientific Reports, Sensors and Medical Physics.

In The Last Decade

Bing Fan

65 papers receiving 1.5k citations

Hit 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.

Diagnosis of the Coronavirus disease (COVID-19): rRT-PCR or CT?

2020 646 citations Qinglin Shen, Bing Fan et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Bing Fan China	13	826	620	224	200	195	72	1.5k
Lu Huang China	14	718 0.9×	607 1.0×	370 1.7×	173 0.9×	149 0.8×	57	1.5k
Sana Salehi United States	12	819 1.0×	691 1.1×	264 1.2×	282 1.4×	156 0.8×	25	1.5k
Yuting Liao China	16	780 0.9×	415 0.7×	162 0.7×	221 1.1×	91 0.5×	82	1.4k
Siu Ting Leung China	4	792 1.0×	458 0.7×	146 0.7×	188 0.9×	170 0.9×	4	1.1k
Wenbing Zeng China	10	770 0.9×	772 1.2×	302 1.3×	170 0.8×	96 0.5×	15	1.3k
Ian Pan United States	14	1.2k 1.4×	410 0.7×	140 0.6×	220 1.1×	357 1.8×	31	1.8k
Qizhi Yu China	12	597 0.7×	751 1.2×	271 1.2×	125 0.6×	184 0.9×	21	1.4k
Ho Yuen Frank Wong China	5	730 0.9×	468 0.8×	154 0.7×	264 1.3×	166 0.9×	9	1.5k
Jonan Chun Yin Lee China	3	774 0.9×	456 0.7×	146 0.7×	184 0.9×	168 0.9×	5	1.1k
Kasey Halsey United States	4	673 0.8×	407 0.7×	117 0.5×	150 0.8×	151 0.8×	6	947

Countries citing papers authored by Bing Fan

Since Specialization

Citations

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

Fields of papers citing papers by Bing Fan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bing Fan

This figure shows the co-authorship network connecting the top 25 collaborators of Bing Fan. A scholar is included among the top collaborators of Bing Fan 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 Bing Fan. Bing Fan 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

Jin, Di, et al.. (2025). Predictive models of epidermal growth factor receptor mutation in lung adenocarcinoma using PET/CT‐based radiomics features. Medical Physics. 52(6). 3697–3710.

Huang, Pei, et al.. (2025). Machine-learning based Computed Tomography Radiomics Nomogram for Predicting Perineural Invasion in Gastric Cancer. Current Medical Imaging Formerly Current Medical Imaging Reviews. 21. e15734056323323–e15734056323323. 1 indexed citations

Zeng, Jie, Dong Wei, Bing Fan, et al.. (2025). Organic small molecule for malignant tumor photothermal / photodynamic and immunotherapy via apoptosis and ferroptosis. European Polymer Journal. 234. 114018–114018. 1 indexed citations

Ma, Yanqing, Bing Fan, Yu Guan, et al.. (2024). CT whole lung radiomic nomogram: a potential biomarker for lung function evaluation and identification of COPD. Military Medical Research. 11(1). 14–14. 12 indexed citations

Guan, Yu, Xiaoqing Lin, Liang Mao, et al.. (2024). CT-based whole lung radiomics nomogram for identification of PRISm from non-COPD subjects. Respiratory Research. 25(1). 329–329. 2 indexed citations

Li, Xiaofen, Jingkun Zhang, Jiaqi Liu, et al.. (2024). Preoperative prediction of histopathological grading in patients with chondrosarcoma using MRI-based radiomics with semantic features. BMC Medical Imaging. 24(1). 171–171. 2 indexed citations

Liu, Ying, Pei Huang, Zhiwei Peng, et al.. (2024). Dual-energy CT Radiomics Combined with Quantitative Parameters for Differentiating Lung Adenocarcinoma From Squamous Cell Carcinoma: A Dual-center Study. Academic Radiology. 32(3). 1675–1684.

Liu, Jizhong, et al.. (2023). Automatic segmentation of brain glioma based on XY-Net. Medical & Biological Engineering & Computing. 62(1). 153–166. 2 indexed citations

Dong, Wentao, Ming Jiang, Sheng Li, et al.. (2023). Value of the application of computed tomography‐based radiomics for preoperative prediction of unfavorable pathology in initial bladder cancer. Cancer Medicine. 12(15). 15868–15880. 3 indexed citations

10.

Huang, Ting, Bing Fan, Rui Zhang, et al.. (2023). Application of DCE-MRI radiomics signature analysis in differentiating molecular subtypes of luminal and non-luminal breast cancer. Frontiers in Medicine. 10. 1140514–1140514. 9 indexed citations

11.

Dong, Wentao, Xiaolian Wang, Shaobo Hu, et al.. (2023). Development and validation of a contrast-enhanced CT-based radiomics nomogram for differentiating mass-like thymic hyperplasia and low-risk thymoma. Journal of Cancer Research and Clinical Oncology. 149(16). 14901–14910. 1 indexed citations

12.

Liu, Jiaqi, et al.. (2023). Development of MRI-based radiomics predictive model for classifying endometrial lesions. Scientific Reports. 13(1). 1590–1590. 6 indexed citations

13.

Fan, Bing, et al.. (2022). Analysis of misdiagnosis and ¹⁸ F-FDG PET/CT findings of lymph node tuberculosis. Journal of X-Ray Science and Technology. 30(5). 941–951. 3 indexed citations

14.

Yu, Qiyun, et al.. (2022). Application of Enhanced T1WI of MRI Radiomics in Glioma Grading. International Journal of Clinical Practice. 2022(1). 3252574–3252574. 14 indexed citations

15.

Pang, Peipei, Jian He, Desheng Zhang, et al.. (2021). Value of radiomics model based on enhanced computed tomography in risk grade prediction of gastrointestinal stromal tumors. Scientific Reports. 11(1). 12009–12009. 17 indexed citations

16.

Lin, Xiaoqi, et al.. (2020). Novel Coronavirus Pneumonia Outbreak in 2019: Computed Tomographic Findings in Two Cases. Korean Journal of Radiology. 21(3). 365–365. 95 indexed citations

17.

Shen, Qinglin, et al.. (2020). 2019 Novel Coronavirus (COVID-19) Pneumonia: Serial Computed Tomography Findings. Korean Journal of Radiology. 21(4). 501–501. 83 indexed citations

18.

Zhang, Hua, Xiaohong Liu, Ming‐Yuan Cheng, et al.. (2020). Dynamic CT assessment of disease change and prognosis of patients with moderate COVID-19 pneumonia. Journal of X-Ray Science and Technology. 28(5). 851–861. 10 indexed citations

19.

Lin, Xiaoqi, Jian He, Peipei Pang, et al.. (2020). Value of MRI Radiomics Based on Enhanced T1WI Images in Prediction of Meningiomas Grade. Academic Radiology. 28(5). 687–693. 42 indexed citations

20.

Fan, Bing, et al.. (2017). Quantitative analysis of contrast-enhanced ultrasound in the dog's acute renal failure. Biomedical Research-tokyo. 28(16). 7137–7141. 1 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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