Vincent Andrearczyk

6.1k citations
55 papers · 1.1k · h-index 19

Impact in

Papers in

Vincent Andrearczyk

51 papers receiving 1.1k citations

Peers

Vincent Andrearczyk
Comparison fields: 5 of 106
  • Health Informatics 78
  • Radiology, Nuclear Medicine and Imaging 563
  • Otorhinolaryngology 97
  • Computer Vision and Pattern Recognition 308
  • Artificial Intelligence 447
Replace Adam P. Harrison with:
Adam P. Harrison United States
Jinzheng Cai United States
Jonas Teuwen Netherlands
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Citations per field
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Citations per year

Countries citing papers authored by Vincent Andrearczyk

Since Specialization
Citations

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

Fields of papers citing papers by Vincent Andrearczyk

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 55 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2021124
2 202275
3 202271
4 202067
5 202165
6 201761
7 201959
8 201853
9
Automatic Segmentation of Head and Neck Tumors and Nodal Metastases in PET-CT scans
202042
10 201840
11 202239
12 201728
13 201827
14 202225
15 202124
16 202024
17 201924
18
Overview of the imageCLEF 2018 caption prediction tasks
201821
19 202320
20 202117

About Vincent Andrearczyk

Vincent Andrearczyk is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence, Computer Vision and Pattern Recognition, Pulmonary and Respiratory Medicine and Biomedical Engineering, having authored 55 papers that have together received 1.1k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (30 papers), AI in cancer detection (23 papers), Medical Imaging Techniques and Applications (11 papers), Explainable Artificial Intelligence (XAI) (8 papers), Digital Imaging for Blood Diseases (7 papers), Lung Cancer Diagnosis and Treatment (7 papers), Head and Neck Cancer Studies (5 papers) and Medical Image Segmentation Techniques (4 papers). The work is most often cited by research in Health Informatics (78 citations), Radiology, Nuclear Medicine and Imaging (563 citations), Otorhinolaryngology (97 citations), Computer Vision and Pattern Recognition (308 citations) and Artificial Intelligence (447 citations). Vincent Andrearczyk has collaborated with scholars based in Switzerland, France and United States. Frequent co-authors include Henning Müller, Adrien Depeursinge, Paul F. Whelan, Valentin Oreiller, Mara Graziani, John O. Prior, Mario Jreige, Manfredo Atzori, Martin Vallières and Hesham Elhalawani. Their work appears in journals such as Scientific Reports, Lecture notes in computer science, Journal of Personalized Medicine, Artificial Intelligence Review and Frontiers in Bioengineering and Biotechnology.

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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