Michael Seo

443 citations
10 papers · 173 · 1 hit paper · h-index 6

Impact in

Papers in

Michael Seo

10 papers receiving 173 citations

Michael Seo's Hit Papers

Developing clinical prediction models: a step-by-step guide 2024 · 73 citations
730+1Years since publication204060

Peers

Michael Seo
Comparison fields: 5 of 77
  • Health Informatics 6
  • Statistics and Probability 30
  • Statistics, Probability and Uncertainty 24
  • Experimental and Cognitive Psychology 26
  • Geriatrics and Gerontology 7
Replace Miriam Hattle with:
Miriam Hattle United Kingdom
Nina Deliu Italy
Barrie Chubb United Kingdom
Nicolás Ballarini Austria
Christopher O’Regan United Kingdom
Mengli Xiao United States
Kaveeta P. Vasisht United States
Joeri Kalter Netherlands
Steven Fox United States
Cynthia DeSouza United States
Michael Seo relative to Miriam Hattle United Kingdom Miriam Hattle's profile →
Citations per field
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Miriam Hattle · 1×
Citations per year

Countries citing papers authored by Michael Seo

Since Specialization
Citations

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

Fields of papers citing papers by Michael Seo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

10 of 10 papers shown
#Work
1
Developing clinical prediction models: a step-by-step guide
Hit paper breakdown →
202473
2 202031
3 202021
4 202318
5 202011
6 202210
7 20224
8 20203
9 20231
10 20221

About Michael Seo

Michael Seo is a scholar working on Statistics and Probability, Statistics, Probability and Uncertainty, Experimental and Cognitive Psychology, Pharmacology and Cognitive Neuroscience, having authored 10 papers that have together received 173 indexed citations. Recurring topics across this work include Meta-analysis and systematic reviews (4 papers), Mental Health Research Topics (3 papers), Statistical Methods in Clinical Trials (3 papers), Statistical Methods and Bayesian Inference (2 papers), Health Systems, Economic Evaluations, Quality of Life (2 papers), Treatment of Major Depression (2 papers), Advanced Causal Inference Techniques (2 papers) and Machine Learning in Healthcare (2 papers). The work is most often cited by research in Health Informatics (6 citations), Statistics and Probability (30 citations), Statistics, Probability and Uncertainty (24 citations), Experimental and Cognitive Psychology (26 citations) and Geriatrics and Gerontology (7 citations). Michael Seo has collaborated with scholars based in Switzerland, United Kingdom and Japan. Frequent co-authors include Orestis Efthimiou, Matthias Egger, Thomas P. A. Debray, Georgia Salanti, Toshi A. Furukawa, Konstantina Chalkou, Ian R. White, Areti Angeliki Veroniki, Anneka Tomlinson and Toby Pillinger. Their work appears in journals such as Statistics in Medicine, Research Synthesis Methods, Statistical Methods in Medical Research, BMJ and Journal of Affective Disorders.

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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