Wang Ya

850 citations
40 papers · 647 indexed · h-index 13

Impact in

    • MRI in cancer diagnosis
    • Radiomics and Machine Learning in Medical Imaging
    • Advanced MRI Techniques and Applications
    • Medical Imaging Techniques and Applications
    • Retinal Imaging and Analysis
    • Head and Neck Cancer Studies

Papers in

Wang Ya

36 papers receiving 637 citations

Peers

Wang Ya
Comparison fields: 5 of 94
  • Radiology, Nuclear Medicine and Imaging 337
  • Otorhinolaryngology 42
  • Health Information Management 23
  • Hepatology 39
  • Ophthalmology 43
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Citations per field
00.5×10.5×
Mingzhe Li · 1×
Citations per year

Countries citing papers authored by Wang Ya

Since Specialization
Citations

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

Fields of papers citing papers by Wang Ya

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Wang Ya, 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 Wang Ya Line = papers co-authored together Wang Ya links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 40 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011117
2 2009103
3 202076
4 200857
5 201845
6 200940
7 202029
8 201723
9 201916
10
20 years experience in chemotherapy of choriocarcinoma and malignant mole.
197914
11 202314
12 201814
13
Regulatory T cells in renal disease.
200812
14 202111
15
Plasma Double-peak Phenomenon Following Oral Administration
20148
16 20208
17 20148
18 20197
19 20137
20 20156

About Wang Ya

Wang Ya is a scholar working on Oncology, Molecular Biology, Surgery, Pulmonary and Respiratory Medicine and Epidemiology, having authored 40 papers that have together received 647 indexed citations. Recurring topics across this work include MRI in cancer diagnosis (4 papers), Advanced MRI Techniques and Applications (3 papers), Immune Cell Function and Interaction (3 papers), Acute Myeloid Leukemia Research (2 papers), Diabetes Treatment and Management (2 papers), Air Quality and Health Impacts (2 papers), COVID-19 Clinical Research Studies (2 papers) and Liver Disease Diagnosis and Treatment (2 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (337 citations), Otorhinolaryngology (42 citations), Health Information Management (23 citations), Hepatology (39 citations) and Ophthalmology (43 citations). Wang Ya has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Jason A. Koutcher, Wei Huang, Howard T. Thaler, Hilda E. Stambuk, Snehal G. Patel, Jatin P. Shah, Amita Shukla‐Dave, Nancy Y. Lee, Lawrence H. Schwartz and David M. Panicek. Their work appears in journals such as International Journal of Biological Macromolecules, Neoplasia, Magnetic Resonance in Medicine, Molecules and Biomedicine & Pharmacotherapy.

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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