Clinton J. Wang

614 total citations · 1 hit paper
6 papers, 456 citations indexed

About

Clinton J. Wang is a scholar working on Radiology, Nuclear Medicine and Imaging, Hepatology and Artificial Intelligence. According to data from OpenAlex, Clinton J. Wang has authored 6 papers receiving a total of 456 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Radiology, Nuclear Medicine and Imaging, 3 papers in Hepatology and 2 papers in Artificial Intelligence. Recurrent topics in Clinton J. Wang's work include Radiomics and Machine Learning in Medical Imaging (4 papers), Hepatocellular Carcinoma Treatment and Prognosis (3 papers) and AI in cancer detection (2 papers). Clinton J. Wang is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (4 papers), Hepatocellular Carcinoma Treatment and Prognosis (3 papers) and AI in cancer detection (2 papers). Clinton J. Wang collaborates with scholars based in United States and Germany. Clinton J. Wang's co-authors include Julius Chapiro, Brian Letzen, James S. Duncan, Charlie Alexander Hamm, Todd Schlachter, Lynn Jeanette Savic, Jeffrey C. Weinreb, Isabel Schobert, MingDe Lin and Marc Ferrante and has published in prestigious journals such as European Radiology, Journal of Vascular and Interventional Radiology and Lecture notes in computer science.

In The Last Decade

Clinton J. Wang

6 papers receiving 446 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.

Deep learning for liver tumor diagnosis part I: development of a convolutional neural network classifier for multi-phasic MRI

2019 245 citations Charlie Alexander Hamm, Clinton J. Wang et al. European Radiology profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Clinton J. Wang United States	4	341	191	155	70	65	6	456
Alexander Ciritsis Switzerland	12	324 1.0×	57 0.3×	194 1.3×	37 0.5×	34 0.5×	38	496
Dooman Arefan United States	14	418 1.2×	53 0.3×	273 1.8×	57 0.8×	42 0.6×	43	597
Liping Yin China	5	242 0.7×	138 0.7×	77 0.5×	87 1.2×	20 0.3×	11	441
Junming Jian China	13	527 1.5×	100 0.5×	147 0.9×	133 1.9×	17 0.3×	22	624
Changzhu Liu China	5	236 0.7×	137 0.7×	77 0.5×	66 0.9×	20 0.3×	9	428
Chih‐Horng Wu Taiwan	11	137 0.4×	138 0.7×	43 0.3×	41 0.6×	14 0.2×	33	376
Paul Jehanno France	4	176 0.5×	56 0.3×	111 0.7×	25 0.4×	31 0.5×	4	249
Ilias Gatos Greece	10	178 0.5×	156 0.8×	64 0.4×	47 0.7×	15 0.2×	20	337
Gil-Sun Hong South Korea	10	149 0.4×	36 0.2×	71 0.5×	48 0.7×	42 0.6×	33	279
Baochun He China	11	193 0.6×	80 0.4×	47 0.3×	103 1.5×	11 0.2×	24	352

Countries citing papers authored by Clinton J. Wang

Since Specialization

Citations

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

Fields of papers citing papers by Clinton J. Wang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Clinton J. Wang

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

All Works

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6 of 6 papers shown

1.

Wang, Clinton J., Lynn Jeanette Savic, Charlie Alexander Hamm, et al.. (2021). Deep learning–assisted differentiation of pathologically proven atypical and typical hepatocellular carcinoma (HCC) versus non-HCC on contrast-enhanced MRI of the liver. European Radiology. 31(7). 4981–4990. 56 indexed citations

2.

Wang, Clinton J., Natalia S. Rost, & Polina Golland. (2020). Spatial-Intensity Transform GANs for High Fidelity Medical Image-to-Image Translation. Lecture notes in computer science. 12262. 749–759. 2 indexed citations

3.

Hamm, Charlie Alexander, Clinton J. Wang, Lynn Jeanette Savic, et al.. (2019). Deep learning for liver tumor diagnosis part I: development of a convolutional neural network classifier for multi-phasic MRI. European Radiology. 29(7). 3338–3347. 245 indexed citations breakdown →

4.

Wang, Clinton J., Charlie Alexander Hamm, Lynn Jeanette Savic, et al.. (2019). Deep learning for liver tumor diagnosis part II: convolutional neural network interpretation using radiologic imaging features. European Radiology. 29(7). 3348–3357. 122 indexed citations

5.

Wang, Clinton J., Charlie Alexander Hamm, Brian Letzen, & James S. Duncan. (2019). A probabilistic approach for interpretable deep learning in liver cancer diagnosis. 29–29. 3 indexed citations

6.

Letzen, Brian, Clinton J. Wang, & Julius Chapiro. (2018). The Role of Artificial Intelligence in Interventional Oncology: A Primer. Journal of Vascular and Interventional Radiology. 30(1). 38–41.e1. 28 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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