J. Wang

447 citations
20 papers · 325 · h-index 6

Impact in

    • Autism Spectrum Disorder Research
    • Neural dynamics and brain function
    • Genetics and Neurodevelopmental Disorders

Papers in

J. Wang

17 papers receiving 320 citations

Peers

J. Wang
Comparison fields: 5 of 78
  • Cognitive Neuroscience 104
  • Genetics 105
  • Cancer Research 35
  • Health Informatics 3
  • Immunology 44
Replace Derek J.C. Tai with:
Derek J.C. Tai United States
Liron Abuhatzira United States
Carol Broadbent United Kingdom
Anna Hackett Australia
Daji Guo China
Huifang Hu China
Ignacio Arias‐Mayenco Spain
Jéssica Molina United States
Joyce So Canada
Yuan Wu China
J. Wang relative to Derek J.C. Tai United States Derek J.C. Tai's profile →
Citations per field
00.5×1.5×2.1×
Derek J.C. Tai · 1×
Citations per year

Countries citing papers authored by J. Wang

Since Specialization
Citations

This map shows the geographic impact of 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 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 J. Wang more than expected).

Fields of papers citing papers by J. Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 2016135
2 1998119
3 201128
4 19999
5 19997
6 19976
7 20215
8 20233
9 20203
10 20162
11 20212
12 20241
13 20211
14 20171
15 20171
16 20191
17 20151
18 20250
19 20240
20 20250

About J. Wang

J. Wang is a scholar working on Biomedical Engineering, Radiology, Nuclear Medicine and Imaging, Molecular Biology, Otorhinolaryngology and Radiation, having authored 20 papers that have together received 325 indexed citations. Recurring topics across this work include Head and Neck Cancer Studies (4 papers), Advanced Radiotherapy Techniques (4 papers), Radiomics and Machine Learning in Medical Imaging (4 papers), Medical Imaging and Analysis (3 papers), Medical Imaging Techniques and Applications (2 papers), Lung Cancer Diagnosis and Treatment (2 papers), Bioinformatics and Genomic Networks (2 papers) and Advanced Sensor and Energy Harvesting Materials (2 papers). The work is most often cited by research in Cognitive Neuroscience (104 citations), Genetics (105 citations), Cancer Research (35 citations), Health Informatics (3 citations) and Immunology (44 citations). J. Wang has collaborated with scholars based in United States and China. Frequent co-authors include Matthew W. Mosconi, Matthew Byerly, Stormi P. White, Lauren E. Ethridge, John A. Sweeney, Dale Newland, Helen H. Hobbs, Vincent Mooser, Santica M. Marcovina and David A. Sanan. Their work appears in journals such as International Journal of Radiation Oncology*Biology*Physics, Nano Energy, Annals of Human Genetics, Biochemical Society Transactions and Human Immunology.

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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