Eugene Tseytlin

985 citations
27 papers · 692 indexed · h-index 15
Topics
Biomedical Text Mining and Ontologies (10 papers)Clinical Reasoning and Diagnostic Skills (10 papers)AI in cancer detection (6 papers)
Partner nations
United StatesCanadaIndia

In The Last Decade

Eugene Tseytlin

27 papers receiving 659 citations

Peers

Eugene Tseytlin
Comparison fields: 5 of 106
  • Artificial Intelligence 341
  • Molecular Biology 171
  • Radiology, Nuclear Medicine and Imaging 133
  • Public Health, Environmental and Occupational Health 107
  • Family Practice 101
Replace Olga Medvedeva with:
Olga Medvedeva United States
Elizabeth Legowski United States
Cord Spreckelsen Germany
Francisco Sendra‐Portero Spain
Steven Bedrick United States
Nikolay S. Markov United States
Rafat Damseh United Arab Emirates
Siddhi Ramesh United States
Eugenio Alberdi United Kingdom
Abhimanyu S. Ahuja United States
Eugene Tseytlin relative to Olga Medvedeva United States Olga Medvedeva's profile →
Citations per field
00.5×3.9×
Olga Medvedeva · 1×
Citations per year

Countries citing papers authored by Eugene Tseytlin

Since Specialization
Citations

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

Fields of papers citing papers by Eugene Tseytlin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Eugene Tseytlin

This figure shows the co-authorship network connecting the top 25 collaborators of Eugene Tseytlin. A scholar is included among the top collaborators of Eugene Tseytlin 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 Eugene Tseytlin. Eugene Tseytlin 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
#WorkIndexed citations
1 65
2 52
3
DeepPhe - A Natural Language Processing System for Extracting Cancer Phenotypes from Clinical Records.
1
4 8
5 72
6 10
7 1
8 8
9 27
10 10
11 37
12
Fostering Diagnostic Accuracy in a Medical Intelligent Tutoring System.
1
13 62
14 42
15 41
16 25
17 39
18 34
19 36
20 62

About Eugene Tseytlin

Eugene Tseytlin is a scholar working on Family Practice, Artificial Intelligence and Statistics, Probability and Uncertainty, having authored 27 papers that have together received 692 indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (10 papers), Clinical Reasoning and Diagnostic Skills (10 papers) and AI in cancer detection (6 papers). The work is most often cited by research in Health Informatics (66 citations), Family Practice (101 citations) and Artificial Intelligence (341 citations). Eugene Tseytlin has collaborated with scholars based in United States, Canada and India. Frequent co-authors include Elizabeth Legowski, Rebecca S. Crowley, Olga Medvedeva, D.M. Jukic, Melissa Castine, Rebecca S. Jacobson, Tanja Bekhuis, Girish Chavan, Kevin J. Mitchell and Roger Azevedo. Their work appears in journals such as PLoS ONE, Cancer Research and BMC Bioinformatics.

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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