Tianyu Tang

44 papers receiving 984 citations

Tianyu Tang's Hit Papers

Predicting Microvascular Invasion in Hepatocellular Carcinoma Using CT-based Radiomics Model 2023 · 138 citations
1380+1+2Years since publication4080120

Peers

Tianyu Tang
Comparison fields: 5 of 83
  • Sensory Systems 112
  • Hepatology 166
  • Neurology 145
  • Cognitive Neuroscience 336
  • Radiology, Nuclear Medicine and Imaging 203
Replace Margaret McKernan with:
Margaret McKernan United Kingdom
Gabriel González‐Escamilla Germany
Niels Allert Germany
Fumio Shima Japan
Akira Yoshikawa Japan
A. Perretti Italy
Manabu Sakuta Japan
Catherine F. Slattery United Kingdom
Marisa Loitfelder Austria
Tianyu Tang relative to Margaret McKernan United Kingdom Margaret McKernan's profile →
Citations per field
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Margaret McKernan · 1×
Citations per year

Countries citing papers authored by Tianyu Tang

Since Specialization
Citations

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

Fields of papers citing papers by Tianyu Tang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Tianyu Tang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Tianyu Tang Line = papers co-authored together Tianyu Tang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 47 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Predicting Microvascular Invasion in Hepatocellular Carcinoma Using CT-based Radiomics Model
Hit paper breakdown →
2023138
2 200983
3 200867
4 201156
5 202349
6 202038
7 202037
8 201935
9 202034
10 202133
11 201932
12 201930
13 201726
14 201924
15 201523
16 201923
17 201923
18 201620
19 202218
20 201818

About Tianyu Tang

Tianyu Tang is a scholar working on Cognitive Neuroscience, Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging, Neurology and Surgery, having authored 47 papers that have together received 995 indexed citations. Recurring topics across this work include Vestibular and auditory disorders (10 papers), Advanced Neuroimaging Techniques and Applications (6 papers), Hearing, Cochlea, Tinnitus, Genetics (5 papers), Acute Ischemic Stroke Management (5 papers), Hepatocellular Carcinoma Treatment and Prognosis (5 papers), Radiomics and Machine Learning in Medical Imaging (5 papers), Neural dynamics and brain function (5 papers) and Functional Brain Connectivity Studies (5 papers). The work is most often cited by research in Sensory Systems (112 citations), Hepatology (166 citations), Neurology (145 citations), Cognitive Neuroscience (336 citations) and Radiology, Nuclear Medicine and Imaging (203 citations). Tianyu Tang has collaborated with scholars based in China, United States and Ireland. Frequent co-authors include Shenghong Ju, Yun Jiao, Yuancheng Wang, Eric J. Lang, Xiaoyan Ke, Zuhong Lu, Timothy A. Blenkinsop, Tianyi Xia, Shanshan Hong and Xiangpan Meng. Their work appears in journals such as Frontiers in Neuroscience, Journal of Magnetic Resonance Imaging, European Radiology, The Journal of Physiology and Radiology.

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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