Feng Pan

6.1k total citations · 2 hit papers
90 papers, 4.1k citations indexed

About

Feng Pan is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Surgery. According to data from OpenAlex, Feng Pan has authored 90 papers receiving a total of 4.1k indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Radiology, Nuclear Medicine and Imaging, 22 papers in Pulmonary and Respiratory Medicine and 18 papers in Surgery. Recurrent topics in Feng Pan's work include COVID-19 Clinical Research Studies (13 papers), COVID-19 diagnosis using AI (10 papers) and Long-Term Effects of COVID-19 (8 papers). Feng Pan is often cited by papers focused on COVID-19 Clinical Research Studies (13 papers), COVID-19 diagnosis using AI (10 papers) and Long-Term Effects of COVID-19 (8 papers). Feng Pan collaborates with scholars based in China, Germany and United States. Feng Pan's co-authors include Lian Yang, Bo Liang, Chuansheng Zheng, Lingli Li, Tianhe Ye, Jiazheng Wang, Dandan Zheng, Richard L. Hesketh, Peng Sun and Ping Zhu and has published in prestigious journals such as Proceedings of the National Academy of Sciences, The Lancet and Advanced Materials.

In The Last Decade

Feng Pan

84 papers receiving 4.0k citations

Hit Papers

Time Course of Lung Changes at Chest CT during Recovery f... 2020 2026 2022 2024 2020 2020 500 1000 1.5k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Feng Pan China 23 1.8k 1.4k 1.0k 809 682 90 4.1k
Xiaoyu Han China 22 2.2k 1.2× 1.4k 1.0× 1.2k 1.2× 797 1.0× 622 0.9× 147 4.4k
Wei Zhao China 32 1.6k 0.9× 2.6k 1.8× 714 0.7× 1.1k 1.4× 599 0.9× 154 4.9k
Yukun Cao China 18 2.0k 1.1× 1.7k 1.2× 1.1k 1.1× 740 0.9× 550 0.8× 81 4.3k
Ali Gholamrezanezhad United States 28 1.5k 0.8× 1.9k 1.4× 707 0.7× 750 0.9× 773 1.1× 215 4.7k
Qian Tao Netherlands 23 2.2k 1.2× 3.2k 2.3× 670 0.7× 554 0.7× 841 1.2× 109 6.1k
Shaolin Li China 27 2.5k 1.3× 3.0k 2.2× 870 0.9× 768 0.9× 870 1.3× 110 6.0k
Tao Ai China 22 2.1k 1.1× 3.4k 2.4× 538 0.5× 636 0.8× 894 1.3× 79 5.5k
Xueyan Mei United States 10 2.1k 1.1× 2.5k 1.8× 690 0.7× 578 0.7× 608 0.9× 29 4.0k
Mingqian Huang United States 16 2.3k 1.2× 2.9k 2.0× 833 0.8× 641 0.8× 699 1.0× 45 4.7k

Countries citing papers authored by Feng Pan

Since Specialization
Citations

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

Fields of papers citing papers by Feng Pan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Feng Pan

This figure shows the co-authorship network connecting the top 25 collaborators of Feng Pan. A scholar is included among the top collaborators of Feng Pan 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 Feng Pan. Feng Pan 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.
Pan, Feng, et al.. (2025). Enhancing Chest X-ray Diagnosis with a Multimodal Deep Learning Network by Integrating Clinical History to Refine Attention. Journal of Imaging Informatics in Medicine. 38(6). 3568–3583.
2.
Pan, Feng, Qiang Zhang, Nanhui Liu, et al.. (2025). Inhalable Lipid Nanoparticles with Mucus Clearance and ROS Scavenging Properties for Acute Lung Injury Treatment. Advanced Functional Materials. 35(48).
3.
Pan, Feng, Qianqian Fan, Zhi Zhang, et al.. (2023). Correction of Arterial-Phase Motion Artifacts in Gadoxetic Acid-Enhanced Liver MRI Using an Innovative Unsupervised Network. Bioengineering. 10(10). 1192–1192. 2 indexed citations
4.
Chen, Yuyang, et al.. (2023). Enhancing Multi-disease Diagnosis of Chest X-rays with Advanced Deep-learning Networks in Real-world Data. Journal of Digital Imaging. 36(4). 1332–1347. 11 indexed citations
5.
Wang, Yuqi, Yunlian Zhou, Feng Pan, & Yingshuo Wang. (2023). An unusual presentation of necrotizing pneumonia caused by foreign body retention in a 20-month-old child: A case report and literature review. Frontiers in Pediatrics. 11. 1203103–1203103. 1 indexed citations
6.
Pan, Feng, Goetz M. Richter, Thuy Duong, et al.. (2022). Treatment of Postoperative Lymphatic Leakage Applying Transpedal Lymphangiography – Experience in 355 Consecutive Patients. RöFo - Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren. 194(6). 634–643. 8 indexed citations
7.
Yang, Lian, Yue Wang, Lin Li, et al.. (2022). C-Arm Cone-Beam CT Virtual Navigation versus Conventional CT Guidance in the Transthoracic Lung Biopsy: A Case-Control Study. Diagnostics. 12(1). 115–115. 10 indexed citations
8.
Chen, Yuyang & Feng Pan. (2022). Multimodal detection of hateful memes by applying a vision-language pre-training model. PLoS ONE. 17(9). e0274300–e0274300. 12 indexed citations
9.
Lu, Xiaoting, Zhenhai Cui, Xiang Ma, et al.. (2022). The association of obesity with the progression and outcome of COVID‐19: The insight from an artificial‐intelligence‐based imaging quantitative analysis on computed tomography. Diabetes/Metabolism Research and Reviews. 38(4). e3519–e3519. 6 indexed citations
10.
Zhang, Han, Kai Liu, Yimou Gong, et al.. (2022). Vitamin C supramolecular hydrogel for enhanced cancer immunotherapy. Biomaterials. 287. 121673–121673. 39 indexed citations
12.
Klotz, Rosa, Feng Pan, Manuel Feißt, et al.. (2021). Therapeutic lymphography for persistent chyle leak after pancreatic surgery. HPB. 24(5). 616–623. 8 indexed citations
13.
Pan, Feng, Lian Yang, Bo Liang, et al.. (2021). Chest CT Patterns from Diagnosis to 1 Year of Follow-up in Patients with COVID-19. Radiology. 302(3). 709–719. 72 indexed citations
14.
Heger, Ulrike, Claudia Mäck, Christine Tjaden, et al.. (2021). Open irreversible electroporation for isolated local recurrence of pancreatic ductal adenocarcinoma after primary surgery. Pancreatology. 21(7). 1349–1355. 2 indexed citations
15.
Fan, Qianqian, Feng Pan, & Lian Yang. (2020). Spontaneous pneumothorax and subpleural bullae in a patient with COVID-19: a 92-day observation. European Journal of Cardio-Thoracic Surgery. 58(4). 858–860. 15 indexed citations
16.
Li, Bin, et al.. (2020). Prediction of Eggplant Leaf Fv/Fm Based on Vis-NIR Spectroscopy. Guangpuxue yu guangpu fenxi. 40(9). 2834. 3 indexed citations
17.
Pan, Feng, Tianhe Ye, Peng Sun, et al.. (2020). Time Course of Lung Changes at Chest CT during Recovery from Coronavirus Disease 2019 (COVID-19). Radiology. 295(3). 715–721. 1928 indexed citations breakdown →
19.
He, Wenqiang, Dong Liu, Feng Pan, et al.. (2014). Novel technique for the treatment of large subcapsular renal hematoma: combined use of percutaneous drainage and urokinase injection. International Urology and Nephrology. 46(9). 1751–1755. 8 indexed citations
20.
Pan, Feng, Stephen L. Mills, & Stephen C. Massey. (2006). Screening of Gap Junction Antagonists. Investigative Ophthalmology & Visual Science. 47(13). 5389–5389. 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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