Wade Menpes-Smith

582 total citations · 1 hit paper
5 papers, 389 citations indexed

About

Wade Menpes-Smith is a scholar working on Radiology, Nuclear Medicine and Imaging, Infectious Diseases and Cellular and Molecular Neuroscience. According to data from OpenAlex, Wade Menpes-Smith has authored 5 papers receiving a total of 389 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Radiology, Nuclear Medicine and Imaging, 1 paper in Infectious Diseases and 1 paper in Cellular and Molecular Neuroscience. Recurrent topics in Wade Menpes-Smith's work include COVID-19 diagnosis using AI (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers) and Retinal Imaging and Analysis (1 paper). Wade Menpes-Smith is often cited by papers focused on COVID-19 diagnosis using AI (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers) and Retinal Imaging and Analysis (1 paper). Wade Menpes-Smith collaborates with scholars based in United Kingdom, China and Norway. Wade Menpes-Smith's co-authors include Guang Yang, Zhangming Niu, Minhao Wang, Yinghui Jiang, Evandro Fei Fang, Jun Xia, Yuan Gao, Shaoping Hu, Xianglu Xiao and Li Lao and has published in prestigious journals such as IEEE Access, Applied Soft Computing and Frontiers in Aging Neuroscience.

In The Last Decade

Wade Menpes-Smith

5 papers receiving 373 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.

Weakly Supervised Deep Learning for COVID-19 Infection Detection and Classification From CT Images

2020 276 citations Shaoping Hu, Yuan Gao et al. IEEE Access profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Wade Menpes-Smith United Kingdom	5	321	200	72	71	37	5	389
Bejoy Abraham India	9	295 0.9×	233 1.2×	33 0.5×	96 1.4×	98 2.6×	17	417
Vaibhav Arora India	7	295 0.9×	201 1.0×	44 0.6×	101 1.4×	41 1.1×	10	404
Hayden Gunraj Canada	6	283 0.9×	190 0.9×	53 0.7×	48 0.7×	38 1.0×	11	317
Jinyu Cong China	7	217 0.7×	144 0.7×	53 0.7×	68 1.0×	27 0.7×	20	310
Utkarsh Sinha India	6	295 0.9×	196 1.0×	44 0.6×	66 0.9×	41 1.1×	13	368
Minhao Wang China	7	286 0.9×	197 1.0×	71 1.0×	55 0.8×	36 1.0×	18	399
Michael J. Horry Australia	5	316 1.0×	207 1.0×	62 0.9×	53 0.7×	55 1.5×	8	378
Manas Saha India	4	288 0.9×	193 1.0×	52 0.7×	66 0.9×	42 1.1×	8	361
Aysen Degerli Finland	7	162 0.5×	84 0.4×	19 0.3×	50 0.7×	30 0.8×	12	237

Countries citing papers authored by Wade Menpes-Smith

Since Specialization

Citations

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

Fields of papers citing papers by Wade Menpes-Smith

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Wade Menpes-Smith. 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 Wade Menpes-Smith. The network helps show where Wade Menpes-Smith may publish in the future.

Co-authorship network of co-authors of Wade Menpes-Smith

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

5 of 5 papers shown

1.

Ye, Qinghao, Yuan Gao, Weiping Ding, et al.. (2021). Robust weakly supervised learning for COVID-19 recognition using multi-center CT images. Applied Soft Computing. 116. 108291–108291. 32 indexed citations

2.

Ma, Huijing, Qinghao Ye, Weiping Ding, et al.. (2021). Can Clinical Symptoms and Laboratory Results Predict CT Abnormality? Initial Findings Using Novel Machine Learning Techniques in Children With COVID-19 Infections. Frontiers in Medicine. 8. 699984–699984. 9 indexed citations

3.

Ye, Qinghao, Yinghui Jiang, Minhao Wang, et al.. (2020). Systematic and Comprehensive Automated Ventricle Segmentation on Ventricle Images of the Elderly Patients: A Retrospective Study. Frontiers in Aging Neuroscience. 12. 618538–618538. 24 indexed citations

4.

Jiang, Mingfeng, Yaming Wang, Bo Wei, et al.. (2020). SARA-GAN: Self-Attention and Relative Average Discriminator Based Generative Adversarial Networks for Fast Compressed Sensing MRI Reconstruction. Frontiers in Neuroinformatics. 14. 611666–611666. 48 indexed citations

5.

Hu, Shaoping, Yuan Gao, Zhangming Niu, et al.. (2020). Weakly Supervised Deep Learning for COVID-19 Infection Detection and Classification From CT Images. IEEE Access. 8. 118869–118883. 276 indexed citations breakdown →

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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