Stein Olav Skrøvseth

1.6k citations
40 papers · 1.0k indexed · h-index 16
Topics
Diabetes Management and Research (6 papers)Machine Learning in Healthcare (6 papers)Mobile Health and mHealth Applications (6 papers)
Partner nations
NorwayUnited StatesSpain

In The Last Decade

Stein Olav Skrøvseth

39 papers receiving 964 citations

Peers

Stein Olav Skrøvseth
Comparison fields: 5 of 131
  • General Health Professions 329
  • Artificial Intelligence 256
  • Oncology 175
  • Endocrinology, Diabetes and Metabolism 139
  • Public Health, Environmental and Occupational Health 121
Replace Lefteris Koumakis with:
Lefteris Koumakis Greece
Wen‐Shan Jian Taiwan
Milensu Shanyinde United Kingdom
Prem Timsina United States
Mostafa Langarizadeh Iran
Jiancheng Ye United States
Taridzo Chomutare Norway
Robert M. Cronin United States
Bilal A. Mateen United Kingdom
Gail Barker United States
Stein Olav Skrøvseth relative to Lefteris Koumakis Greece Lefteris Koumakis's profile →
Citations per field
00.5×2.6×
Lefteris Koumakis · 1×
Citations per year

Countries citing papers authored by Stein Olav Skrøvseth

Since Specialization
Citations

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

Fields of papers citing papers by Stein Olav Skrøvseth

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Stein Olav Skrøvseth. 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 Stein Olav Skrøvseth. The network helps show where Stein Olav Skrøvseth may publish in the future.

Co-authorship network of co-authors of Stein Olav Skrøvseth

This figure shows the co-authorship network connecting the top 25 collaborators of Stein Olav Skrøvseth. A scholar is included among the top collaborators of Stein Olav Skrøvseth 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 Stein Olav Skrøvseth. Stein Olav Skrøvseth 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 15
2 48
3 54
4 7
5 90
6 51
7
Learning similarities between irregularly sampled short multivariate time series from EHRs
3
8 37
9 5
10 2
11 50
12 59
13 6
14 32
15 9
16 22
17 2
18 156
19 11
20 7

About Stein Olav Skrøvseth

Stein Olav Skrøvseth is a scholar working on Artificial Intelligence, Endocrinology, Diabetes and Metabolism and General Health Professions, having authored 40 papers that have together received 1.0k indexed citations. Recurring topics across this work include Diabetes Management and Research (6 papers), Machine Learning in Healthcare (6 papers) and Mobile Health and mHealth Applications (6 papers). The work is most often cited by research in Health Informatics (60 citations), Applied Psychology (90 citations) and Health Information Management (61 citations). Stein Olav Skrøvseth has collaborated with scholars based in Norway, United States and Spain. Frequent co-authors include Fred Godtliebsen, Eirik Årsand, Gunnar Hartvigsen, Rolv‐Ole Lindsetmo, Naoe Tatara, Knut Magne Augestad, Cristina Soguero-Ruíz, Stephen D. Bartlett, Taridzo Chomutare and Dag Helge Frøisland. Their work appears in journals such as PLoS ONE, Scientific Reports and Physical Review A.

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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