Jonathan M. Tan

33 papers receiving 425 citations

Jonathan M. Tan's Hit Papers

Co-Intelligence: Living and Working with AI 2025 · 30 citations
300Years since publication102030

Peers

Jonathan M. Tan
Comparison fields: 5 of 93
  • Anesthesiology and Pain Medicine 69
  • Health Informatics 10
  • Obstetrics and Gynecology 51
  • Critical Care and Intensive Care Medicine 30
  • Surgery 205
Replace D. J. N. Wong with:
D. J. N. Wong United Kingdom
Petr Štourač Czechia
David J. Annibale United States
Michelle Simon United States
Bhavani Shankar Kodali United States
William R. Hand United States
Mohammed Minhaj United States
Frank Stueber Switzerland
Jacob P. VanHouten United States
Anju Grewal India
Jonathan M. Tan relative to D. J. N. Wong United Kingdom D. J. N. Wong's profile →
Citations per field
00.5×3.3×
D. J. N. Wong · 1×
Citations per year

Countries citing papers authored by Jonathan M. Tan

Since Specialization
Citations

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

Fields of papers citing papers by Jonathan M. Tan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jonathan M. Tan. 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 Jonathan M. Tan. The network helps show where Jonathan M. Tan may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 38 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201061
2 201641
3 202039
4 201034
5
Co-Intelligence: Living and Working with AI
Hit paper breakdown →
202530
6 201929
7 201328
8 201021
9 201421
10 201915
11 200814
12 201711
13 202210
14 201310
15 201610
16 20108
17 20198
18 20177
19 20207
20 20196

About Jonathan M. Tan

Jonathan M. Tan is a scholar working on Surgery, Cardiology and Cardiovascular Medicine, Anesthesiology and Pain Medicine, Pediatrics, Perinatology and Child Health and Health Information Management, having authored 38 papers that have together received 438 indexed citations. Recurring topics across this work include Cardiac, Anesthesia and Surgical Outcomes (8 papers), Healthcare Technology and Patient Monitoring (5 papers), Electronic Health Records Systems (4 papers), Anesthesia and Pain Management (4 papers), Airway Management and Intubation Techniques (3 papers), Pediatric Pain Management Techniques (2 papers), Anesthesia and Neurotoxicity Research (2 papers) and Tracheal and airway disorders (2 papers). The work is most often cited by research in Anesthesiology and Pain Medicine (69 citations), Health Informatics (10 citations), Obstetrics and Gynecology (51 citations), Critical Care and Intensive Care Medicine (30 citations) and Surgery (205 citations). Jonathan M. Tan has collaborated with scholars based in United States, United Kingdom and Argentina. Frequent co-authors include Alex Macario, Allan F. Simpao, Jorge A. Gálvez, Christopher Gallagher, Yasser Y. El‐Sayed, Brendan Carvalho, Maurice L. Druzin, Jack O. Wasey, HeiShun Yu and William H. Moore. Their work appears in journals such as Anesthesia & Analgesia, Anesthesiology, Pediatric Anesthesia, The Journal of Pediatrics and IEEE Electron Device Letters.

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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