Thomas Chong

859 citations
9 papers · 615 · 1 hit paper · h-index 6

Impact in

Papers in

    • RNA Interference and Gene Delivery 2
    • Mitochondrial Function and Pathology 1
    • Tissue Engineering and Regenerative Medicine 2

Thomas Chong

9 papers receiving 603 citations

Thomas Chong's Hit Papers

Virtual histological staining of unlabelled tissue-autofluorescence images via deep learning 2019 · 442 citations
4420+2+4Years since publication100200300400

Peers

Thomas Chong
Comparison fields: 5 of 94
  • Biophysics 210
  • Geriatrics and Gerontology 47
  • Acoustics and Ultrasonics 10
  • Media Technology 84
  • Structural Biology 9
Replace Linjing Fang with:
Linjing Fang United States
Refaat E. Gabr United States
Mary M. Maleckar Norway
Hyungjoo Cho South Korea
Seungyoon B. Yu United States
Niklas Köhler Germany
Thomas Ach Germany
Claire Lifan Chen United States
Mohamed A. Naser United States
Karl St‐Arnaud Canada
Thomas Chong relative to Linjing Fang United States Linjing Fang's profile →
Citations per field
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Citations per year

Countries citing papers authored by Thomas Chong

Since Specialization
Citations

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

Fields of papers citing papers by Thomas Chong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

9 of 9 papers shown
#Work
1
Virtual histological staining of unlabelled tissue-autofluorescence images via deep learning
Hit paper breakdown →
2019442
2 201878
3 201631
4 201928
5 202022
6 20197
7 20233
8 20133
9 20131

About Thomas Chong

Thomas Chong is a scholar working on Molecular Biology, Surgery, Endocrinology, Diabetes and Metabolism, Physiology and Cellular and Molecular Neuroscience, having authored 9 papers that have together received 615 indexed citations. Recurring topics across this work include Biochemical effects in animals (2 papers), RNA Interference and Gene Delivery (2 papers), Tissue Engineering and Regenerative Medicine (2 papers), Alzheimer's disease research and treatments (1 paper), Neurogenesis and neuroplasticity mechanisms (1 paper), Animal Genetics and Reproduction (1 paper), Mitochondrial Function and Pathology (1 paper) and Clinical Reasoning and Diagnostic Skills (1 paper). The work is most often cited by research in Biophysics (210 citations), Geriatrics and Gerontology (47 citations), Acoustics and Ultrasonics (10 citations), Media Technology (84 citations) and Structural Biology (9 citations). Thomas Chong has collaborated with scholars based in United States and Australia. Frequent co-authors include Anthony Sisk, Jonathan E. Zuckerman, William D. Wallace, Lindsey Westbrook, Yair Rivenson, Yichen Wu, Zhensong Wei, Kevin de Haan, Yibo Zhang and Harun Günaydın. Their work appears in journals such as Journal of Visualized Experiments, Clinical Chemistry, Nature Biomedical Engineering, Current Alzheimer Research and Scientific Reports.

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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