Michael C. Jin

4.8k citations
75 papers · 1.3k · h-index 15

Impact in

Papers in

Michael C. Jin

67 papers receiving 1.2k citations

Peers

Michael C. Jin
Comparison fields: 5 of 144
  • Human-Computer Interaction 222
  • Genetics 177
  • Health Informatics 12
  • Pathology and Forensic Medicine 154
  • Endocrinology, Diabetes and Metabolism 139
Replace Jay J. Han with:
Jay J. Han United States
Daniel T. Nagasawa United States
Sara Mariani United States
Sandrine de Ribaupierre Canada
Ivar Mendez Canada
Marialuisa Martelli Italy
Carlito Lagman United States
Shin Saito Japan
Rebecca Pauly United States
Wei‐Chen Lin Taiwan
Michael C. Jin relative to Jay J. Han United States Jay J. Han's profile →
Citations per field
00.5×3.5×
Jay J. Han · 1×
Citations per year

Countries citing papers authored by Michael C. Jin

Since Specialization
Citations

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

Fields of papers citing papers by Michael C. Jin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 75 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2008357
2 2019118
3 2019100
4 201673
5 201650
6 202042
7 201939
8 202025
9 202323
10 201921
11 202020
12 202216
13 201915
14 202015
15 202014
16 202214
17 201914
18 202014
19 200813
20 202012

About Michael C. Jin

Michael C. Jin is a scholar working on Genetics, Pathology and Forensic Medicine, Neurology, Surgery and Epidemiology, having authored 75 papers that have together received 1.3k indexed citations. Recurring topics across this work include Glioma Diagnosis and Treatment (12 papers), Cancer Genomics and Diagnostics (10 papers), Lymphoma Diagnosis and Treatment (8 papers), Meningioma and schwannoma management (7 papers), Opioid Use Disorder Treatment (7 papers), Musculoskeletal pain and rehabilitation (6 papers), Brain Metastases and Treatment (5 papers) and Spine and Intervertebral Disc Pathology (5 papers). The work is most often cited by research in Human-Computer Interaction (222 citations), Genetics (177 citations), Health Informatics (12 citations), Pathology and Forensic Medicine (154 citations) and Endocrinology, Diabetes and Metabolism (139 citations). Michael C. Jin has collaborated with scholars based in United States, Germany and Switzerland. Frequent co-authors include Jeremy N. Bailenson, Nick Yee, Jim Blascovich, Andrew C. Beall, Uchechukwu C. Megwalu, Z. Jason Qian, Tej D. Azad, Anand Veeravagu, Kara D. Meister and Zachary A. Medress. Their work appears in journals such as Blood, World Neurosurgery, Neurosurgical FOCUS, Journal of Neurosurgery Pediatrics and The Laryngoscope.

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.

Explore authors with similar magnitude of impact