Feng Feng

42 total papers · 477 total citations
30 papers, 293 citations indexed

About

Feng Feng is a scholar working on Biomedical Engineering, Radiology, Nuclear Medicine and Imaging and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Feng Feng has authored 30 papers receiving a total of 293 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Biomedical Engineering, 8 papers in Radiology, Nuclear Medicine and Imaging and 6 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Feng Feng's work include Nanoplatforms for cancer theranostics (6 papers), Radiomics and Machine Learning in Medical Imaging (5 papers) and Ovarian cancer diagnosis and treatment (5 papers). Feng Feng is often cited by papers focused on Nanoplatforms for cancer theranostics (6 papers), Radiomics and Machine Learning in Medical Imaging (5 papers) and Ovarian cancer diagnosis and treatment (5 papers). Feng Feng collaborates with scholars based in China, United States and United Kingdom. Feng Feng's co-authors include Jinwei Qiang, Guofu Zhang, Shu Hui Zhao, Hua Feng, Yongai Li, Haiming Li, Shuhui Zhao, Wei Gu, Zhiyong Zhang and Junming Jian and has published in prestigious journals such as Nano Letters, ACS Nano and PLoS ONE.

In The Last Decade

Feng Feng

27 papers receiving 290 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Feng Feng	188	102	66	49	38	30	293
Annabel Spek	88 0.5×	40 0.4×	53 0.8×	103 2.1×	56 1.5×	28	297
Fabio Stefano Frech	48 0.3×	35 0.3×	62 0.9×	48 1.0×	13 0.3×	23	335
Mohamed Zaitoun	58 0.3×	131 1.3×	113 1.7×	61 1.2×	9 0.2×	27	283
Azmat Sadozye	93 0.5×	44 0.4×	64 1.0×	56 1.1×	26 0.7×	24	249
Hongjie Fan	29 0.2×	59 0.6×	81 1.2×	32 0.7×	119 3.1×	30	320
Chang Kyu Sung	74 0.4×	49 0.5×	41 0.6×	115 2.3×	52 1.4×	30	313
Jeffrey Lin	116 0.6×	61 0.6×	81 1.2×	64 1.3×	29 0.8×	20	365
Joanna G. Escalon	136 0.7×	25 0.2×	30 0.5×	144 2.9×	20 0.5×	34	309
Nicola Maria Lucarelli	41 0.2×	31 0.3×	28 0.4×	90 1.8×	6 0.2×	33	255
Ken Makihara	45 0.2×	128 1.3×	184 2.8×	36 0.7×	17 0.4×	34	314

Countries citing papers authored by Feng Feng

Since Specialization

Citations

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

Fields of papers citing papers by Feng Feng

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Feng Feng

This figure shows the co-authorship network connecting the top 25 collaborators of Feng Feng. A scholar is included among the top collaborators of Feng Feng 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 Feng. Feng Feng is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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