Hongna Tan

43 total papers · 956 total citations
29 papers, 680 citations indexed

About

Hongna Tan is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Cancer Research. According to data from OpenAlex, Hongna Tan has authored 29 papers receiving a total of 680 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Radiology, Nuclear Medicine and Imaging, 9 papers in Artificial Intelligence and 7 papers in Cancer Research. Recurrent topics in Hongna Tan's work include Radiomics and Machine Learning in Medical Imaging (15 papers), MRI in cancer diagnosis (10 papers) and AI in cancer detection (9 papers). Hongna Tan is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (15 papers), MRI in cancer diagnosis (10 papers) and AI in cancer detection (9 papers). Hongna Tan collaborates with scholars based in China and Canada. Hongna Tan's co-authors include Meiyun Wang, Jinjin Hai, Jing Zhou, Yaping Wu, Minghui Wu, Huijuan Xiao, Peigang Ning, Dapeng Shi, Jian Chen and Shewei Dou and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Medicine.

In The Last Decade

Hongna Tan

25 papers receiving 671 citations

Author Peers

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

Author						Papers	Cites
Hongna Tan	425	187	145	124	113	29	680
João V. Horvat	479 1.1×	128 0.7×	72 0.5×	64 0.5×	95 0.8×	29	638
Yini Huang	489 1.2×	264 1.4×	95 0.7×	48 0.4×	65 0.6×	23	657
Xueyi Zheng	416 1.0×	227 1.2×	94 0.6×	54 0.4×	72 0.6×	15	599
Francesca Patella	224 0.5×	146 0.8×	58 0.4×	36 0.3×	176 1.6×	24	634
Hwa‐Koon Wu	189 0.4×	69 0.4×	246 1.7×	188 1.5×	68 0.6×	45	644
Richard Colling	262 0.6×	315 1.7×	122 0.8×	102 0.8×	17 0.2×	47	760
Chiara Trentin	148 0.3×	74 0.4×	134 0.9×	146 1.2×	31 0.3×	44	613
Hongkun Yin	269 0.6×	75 0.4×	94 0.6×	48 0.4×	21 0.2×	41	576
Zeyan Xu	413 1.0×	282 1.5×	68 0.5×	32 0.3×	28 0.2×	41	707
Francesca Galati	313 0.7×	35 0.2×	100 0.7×	58 0.5×	159 1.4×	34	620

Countries citing papers authored by Hongna Tan

Since Specialization

Citations

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

Fields of papers citing papers by Hongna Tan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hongna Tan

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