Stavros Archondakis

544 total citations
35 papers, 250 citations indexed

About

Stavros Archondakis is a scholar working on Artificial Intelligence, Epidemiology and Surgery. According to data from OpenAlex, Stavros Archondakis has authored 35 papers receiving a total of 250 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 12 papers in Epidemiology and 8 papers in Surgery. Recurrent topics in Stavros Archondakis's work include AI in cancer detection (14 papers), Cervical Cancer and HPV Research (8 papers) and Clinical Laboratory Practices and Quality Control (8 papers). Stavros Archondakis is often cited by papers focused on AI in cancer detection (14 papers), Cervical Cancer and HPV Research (8 papers) and Clinical Laboratory Practices and Quality Control (8 papers). Stavros Archondakis collaborates with scholars based in Greece, United States and United Kingdom. Stavros Archondakis's co-authors include Stamatis Katsenos, Petros Karakitsos, Ioannis Panayiotides, George Peros, Antigoni Lekka, Μaria Dalamaga, George Sotiropoulos, Κωνσταντίνος Καρμανιώλας, Evangelia Papadavid and Abraham Pouliakis and has published in prestigious journals such as Maturitas, Telemedicine Journal and e-Health and Journal of Telemedicine and Telecare.

In The Last Decade

Stavros Archondakis

33 papers receiving 247 citations

Peers

Stavros Archondakis
Comparison fields: 5 of 52
  • Epidemiology 120
  • Artificial Intelligence 79
  • Oncology 77
  • Surgery 42
  • Pulmonary and Respiratory Medicine 34
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Citations per field, relative to Stavros Archondakis
Stavros Archondakis · 1×
Citations per year, relative to Stavros Archondakis
Stavros Archondakis · 1×

Countries citing papers authored by Stavros Archondakis

Since Specialization
Citations

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

Fields of papers citing papers by Stavros Archondakis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Stavros Archondakis

This figure shows the co-authorship network connecting the top 25 collaborators of Stavros Archondakis. A scholar is included among the top collaborators of Stavros Archondakis based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Stavros Archondakis. Stavros Archondakis is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
# Work Indexed citations
1 2
2 6
3 7
4 6
5 2
6 1
7 9
8 9
9 5
10 6
11 11
12 2
13 52
14 4
15 9
16 22
17 7
18 38
19 3
20
The potential of tree classifiers on the cytological examination of gastric lesions
4

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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