Kira Radinsky

2.6k citations
62 papers · 1.5k · h-index 21

Impact in

    • Topic Modeling
    • Natural Language Processing Techniques
    • Advanced Text Analysis Techniques
    • Web Data Mining and Analysis
    • Information Retrieval and Search Behavior

Papers in

Kira Radinsky

58 papers receiving 1.5k citations

Peers

Kira Radinsky
Comparison fields: 5 of 125
  • Artificial Intelligence 811
  • Information Systems 351
  • Health Informatics 17
  • Health Information Management 55
  • Signal Processing 131
Replace Haishuai Wang with:
Haishuai Wang China
Chengsheng Mao United States
Jun Yan China
Satya S. Sahoo United States
Jia Rong Australia
Alper Kürşat Uysal Türkiye
Sivaji Bandyopadhyay India
Bo Jin China
Carsten Eickhoff United States
Wessel Kraaij Netherlands
Kira Radinsky relative to Haishuai Wang China Haishuai Wang's profile →
Citations per field
00.5×11.8×
Haishuai Wang · 1×
Citations per year

Countries citing papers authored by Kira Radinsky

Since Specialization
Citations

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

Fields of papers citing papers by Kira Radinsky

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 62 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011257
2 2012137
3 2013127
4 2019100
5 201286
6 201285
7 202058
8 201450
9 202042
10 201839
11 201335
12 201335
13 202235
14 201835
15 202029
16 200829
17 202125
18 201924
19 201924
20 201922

About Kira Radinsky

Kira Radinsky is a scholar working on Artificial Intelligence, Information Systems, Cardiology and Cardiovascular Medicine, Molecular Biology and Computational Theory and Mathematics, having authored 62 papers that have together received 1.5k indexed citations. Recurring topics across this work include Topic Modeling (13 papers), Advanced Text Analysis Techniques (13 papers), Web Data Mining and Analysis (12 papers), Computational Drug Discovery Methods (8 papers), ECG Monitoring and Analysis (7 papers), Information Retrieval and Search Behavior (5 papers), Biomedical Text Mining and Ontologies (5 papers) and Machine Learning in Materials Science (5 papers). The work is most often cited by research in Artificial Intelligence (811 citations), Information Systems (351 citations), Health Informatics (17 citations), Health Information Management (55 citations) and Signal Processing (131 citations). Kira Radinsky has collaborated with scholars based in Israel, United States and United Kingdom. Frequent co-authors include Shaul Markovitch, Eric Horvitz, Tomer Golany, Eugene Agichtein, Evgeniy Gabrilovich, Milad Shokouhi, Gideon Koren, Ido Guy, Varda Shalev and Guy Rosin. Their work appears in journals such as Pharmacology Research & Perspectives, ACM SIGIR Forum, Bioinformatics, Journal of the American Medical Informatics Association and ACM Transactions on Information Systems.

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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