Patrick Paczkowski

820 citations
14 papers · 501 · h-index 10

Impact in

Papers in

    • CAR-T cell therapy research 7
    • Cancer Immunotherapy and Biomarkers 2
    • Immunotherapy and Immune Responses 4
    • Immune Cell Function and Interaction 3

Patrick Paczkowski

14 papers receiving 480 citations

Peers

Patrick Paczkowski
Comparison fields: 5 of 60
  • Oncology 315
  • Human-Computer Interaction 47
  • Immunology 141
  • Computer Graphics and Computer-Aided Design 23
  • Biomedical Engineering 103
Replace Kevin Tong with:
Kevin Tong United States
Hanlin Yin China
Duy Pham United States
Ulrich Canzler Germany
Bailin He China
Akinori Sasaki Japan
Takuya Sueyoshi Japan
Toshikage Nagao Japan
Edris A.F. Mahtab Netherlands
Oscar Persson Sweden
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Citations per field
00.5×10.3×
Kevin Tong · 1×
Citations per year

Countries citing papers authored by Patrick Paczkowski

Since Specialization
Citations

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

Fields of papers citing papers by Patrick Paczkowski

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

14 of 14 papers shown
#Work
1 2018229
2 201796
3 201930
4 201126
5 201825
6 201122
7 201420
8 202019
9 202013
10 201710
11 20175
12 20184
13 20171
14 20171

About Patrick Paczkowski

Patrick Paczkowski is a scholar working on Oncology, Immunology, Molecular Biology, Computer Vision and Pattern Recognition and Aerospace Engineering, having authored 14 papers that have together received 501 indexed citations. Recurring topics across this work include CAR-T cell therapy research (7 papers), Immunotherapy and Immune Responses (4 papers), Single-cell and spatial transcriptomics (3 papers), Immune Cell Function and Interaction (3 papers), 3D Surveying and Cultural Heritage (2 papers), Interactive and Immersive Displays (2 papers), Advanced Vision and Imaging (2 papers) and Cancer Immunotherapy and Biomarkers (2 papers). The work is most often cited by research in Oncology (315 citations), Human-Computer Interaction (47 citations), Immunology (141 citations), Computer Graphics and Computer-Aided Design (23 citations) and Biomedical Engineering (103 citations). Patrick Paczkowski has collaborated with scholars based in United States, South Korea and Ireland. Frequent co-authors include Sean Mackay, Jing Zhou, Colin Ng, Rong Fan, Alaina Kaiser, James R. Heath, Brianna Flynn, Adrian Bot, John M. Rossi and Yueh-wei Shen. Their work appears in journals such as Blood, Journal of Clinical Oncology, Journal for ImmunoTherapy of Cancer, IEEE Transactions on Visualization and Computer Graphics and ACM Transactions on Graphics.

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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