Igor Cichecki

807 citations
3 papers · 500 · 1 hit paper · h-index 2

Impact in

    • Artificial Intelligence in Healthcare and Education
    • Topic Modeling
    • AI in Service Interactions
    • Sentiment Analysis and Opinion Mining
    • Natural Language Processing Techniques

Papers in

Igor Cichecki

2 papers receiving 468 citations

Igor Cichecki's Hit Papers

ChatGPT: Jack of all trades, master of none 2023 · 488 citations
4880+1+2Years since publication100200300400

Peers

Igor Cichecki
Comparison fields: 5 of 87
  • Health Informatics 137
  • Artificial Intelligence 276
  • Computer Science Applications 43
  • Safety Research 34
  • General Social Sciences 13
Replace Mateusz Kochanek with:
Mateusz Kochanek Poland
Oliwier Kaszyca Poland
Łukasz Radliński Poland
Bartłomiej Koptyra Poland
Konrad Wojtasik Poland
Julita Bielaniewicz Poland
Marcin Oleksy Poland
Arkadiusz Janz Poland
Kamil Kanclerz Poland
Stanisław Woźniak Poland
Igor Cichecki relative to Mateusz Kochanek Poland Mateusz Kochanek's profile →
Citations per field
00.5×1.5×
Mateusz Kochanek · 1×
Citations per year

Countries citing papers authored by Igor Cichecki

Since Specialization
Citations

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

Fields of papers citing papers by Igor Cichecki

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 18 scholars most cited alongside Igor Cichecki, 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 Igor Cichecki Line = papers co-authored together Igor Cichecki links everyone, so they are left out of the graph.

All Works

3 of 3 papers shown
#Work
1
ChatGPT: Jack of all trades, master of none
Hit paper breakdown →
2023488
2 202412
3 20250

About Igor Cichecki

Igor Cichecki is a scholar working on Health Informatics, Radiology, Nuclear Medicine and Imaging, Communication, Artificial Intelligence and Insect Science, having authored 3 papers that have together received 500 indexed citations. Recurring topics across this work include Topic Modeling (2 papers), COVID-19 diagnosis using AI (2 papers), Artificial Intelligence in Healthcare and Education (2 papers) and Public Relations and Crisis Communication (1 paper). The work is most often cited by research in Health Informatics (137 citations), Artificial Intelligence (276 citations), Computer Science Applications (43 citations), Safety Research (34 citations) and General Social Sciences (13 citations). Igor Cichecki has collaborated with scholars based in Poland and Canada. Frequent co-authors include Jan Kocoń, Przemysław Kazienko, Mateusz Kochanek, Oliwier Kaszyca, Marcin Oleksy, Marcin Gruza, Arkadiusz Janz, A. Kocoń, Maciej Piasecki and Piotr Miłkowski. Their work appears in journals such as Journal of Contingencies and Crisis Management, Electronics and Information Fusion.

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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