Beiyi Shen

864 total citations
9 papers, 238 citations indexed

About

Beiyi Shen is a scholar working on Radiology, Nuclear Medicine and Imaging, Infectious Diseases and Genetics. According to data from OpenAlex, Beiyi Shen has authored 9 papers receiving a total of 238 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Radiology, Nuclear Medicine and Imaging, 3 papers in Infectious Diseases and 2 papers in Genetics. Recurrent topics in Beiyi Shen's work include COVID-19 diagnosis using AI (5 papers), COVID-19 Clinical Research Studies (3 papers) and Radiomics and Machine Learning in Medical Imaging (2 papers). Beiyi Shen is often cited by papers focused on COVID-19 diagnosis using AI (5 papers), COVID-19 Clinical Research Studies (3 papers) and Radiomics and Machine Learning in Medical Imaging (2 papers). Beiyi Shen collaborates with scholars based in United States and Canada. Beiyi Shen's co-authors include Timothy Q. Duong, Almas Abbasi, Haifang Li, Jocelyn Zhu, Lanying Wang, Zijin Lin, Audrey G. Chung, Alexander Wong, Henry C. Thode and Wei Hou and has published in prestigious journals such as PLoS ONE, Scientific Reports and Clinical Cancer Research.

In The Last Decade

Beiyi Shen

8 papers receiving 233 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Beiyi Shen United States	6	169	61	59	37	32	9	238
Wei-Lin Chen Taiwan	7	169 1.0×	40 0.7×	69 1.2×	17 0.5×	19 0.6×	9	342
Mishka Gidwani United States	5	315 1.9×	143 2.3×	107 1.8×	27 0.7×	88 2.8×	7	480
Kexue Deng China	8	231 1.4×	63 1.0×	83 1.4×	17 0.5×	45 1.4×	29	302
Ahmed Alksas United States	10	211 1.2×	73 1.2×	72 1.2×	5 0.1×	23 0.7×	40	330
Elina Stoffel United States	7	112 0.7×	117 1.9×	35 0.6×	31 0.8×	27 0.8×	9	330
Mayidili Nijiati China	10	157 0.9×	34 0.6×	35 0.6×	39 1.1×	19 0.6×	22	239
Ryo Shimoyama Japan	8	169 1.0×	81 1.3×	161 2.7×	10 0.3×	55 1.7×	13	394
Wonho Lee South Korea	5	96 0.6×	29 0.5×	36 0.6×	14 0.4×	12 0.4×	14	367
Guillaume Chabin United States	7	240 1.4×	65 1.1×	118 2.0×	18 0.5×	36 1.1×	11	297

Countries citing papers authored by Beiyi Shen

Since Specialization

Citations

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

Fields of papers citing papers by Beiyi Shen

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Beiyi Shen

This figure shows the co-authorship network connecting the top 25 collaborators of Beiyi Shen. A scholar is included among the top collaborators of Beiyi Shen 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 Beiyi Shen. Beiyi Shen 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:

9 of 9 papers shown

1.

Shen, Beiyi, Wei Hou, Haifang Li, et al.. (2023). Longitudinal Chest X-ray Scores and their Relations with Clinical Variables and Outcomes in COVID-19 Patients. Diagnostics. 13(6). 1107–1107. 5 indexed citations

2.

Shen, Beiyi, et al.. (2022). Emphysematous Osteomyelitis: Novel Use of PET-MRI and a Review ofCharacteristic Imaging Findings. Current Medical Imaging Formerly Current Medical Imaging Reviews. 19(10). 1214–1218.

3.

Shen, Beiyi, Almas Abbasi, Adam J. Singer, et al.. (2021). Initial chest radiograph scores inform COVID-19 status, intensive care unit admission and need for mechanical ventilation. Clinical Radiology. 76(6). 473.e1–473.e7. 22 indexed citations

4.

Wong, Alexander, Zijin Lin, Lanying Wang, et al.. (2021). Towards computer-aided severity assessment via deep neural networks for geographic and opacity extent scoring of SARS-CoV-2 chest X-rays. Scientific Reports. 11(1). 9315–9315. 38 indexed citations

5.

Shen, Beiyi, Gülce Askin, Andrew D. Schweitzer, et al.. (2021). A specific biomarker for amyotrophic lateral sclerosis: Quantitative susceptibility mapping. Clinical Imaging. 75. 125–130. 12 indexed citations

6.

Zhu, Jocelyn, et al.. (2020). Deep-learning convolutional neural networks with transfer learning accurately classify COVID-19 lung infection on portable chest radiographs. PeerJ. 8. e10309–e10309. 30 indexed citations

7.

Zhu, Jocelyn, et al.. (2020). Deep transfer learning artificial intelligence accurately stages COVID-19 lung disease severity on portable chest radiographs. PLoS ONE. 15(7). e0236621–e0236621. 106 indexed citations

8.

Shen, Beiyi. (2020). The Saponin Composition of Common Canadian Pulses. University of Alberta Library. 2 indexed citations

9.

Rajappa, Prajwal, William S. Cobb, Yujie Huang, et al.. (2016). Malignant Astrocytic Tumor Progression Potentiated by JAK-mediated Recruitment of Myeloid Cells. Clinical Cancer Research. 23(12). 3109–3119. 23 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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