Mitchell Tang

15 papers receiving 2.5k citations

Mitchell Tang's Hit Papers

Genetic meta-analysis of diagnosed Alzheimer’s disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing 2019 · 2.1k citations
2.1k0+2+4Years since publication5001k1.5k2k

Peers

Mitchell Tang
Comparison fields: 5 of 98
  • Physiology 1.2k
  • Psychiatry and Mental health 773
  • Neurology 258
  • Health Informatics 51
  • Genetics 438
Replace Alyssa Aguirre with:
Alyssa Aguirre United States
Ellen Elisa De Roeck Belgium
Mona A Kaleem United States
Doris G. Leung United States
Henri Bailly France
David Hart United States
Pascual Sánchez‐Juan Spain
Rawan M. Tarawneh United States
Marcus Naymik United States
Merel O. Mol Netherlands
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Citations per year

Countries citing papers authored by Mitchell Tang

Since Specialization
Citations

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

Fields of papers citing papers by Mitchell Tang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

17 of 17 papers shown
#Work
1
Genetic meta-analysis of diagnosed Alzheimer’s disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing
Hit paper breakdown →
20192140
2 2021138
3 201841
4 202233
5 202228
6 201921
7 202420
8 202219
9 202318
10 202213
11 20228
12 20146
13 20244
14 20231
15 20251
16 20251
17 20250

About Mitchell Tang

Mitchell Tang is a scholar working on Health Information Management, Public Health, Environmental and Occupational Health, Physiology, Psychiatry and Mental health and Economics and Econometrics, having authored 17 papers that have together received 2.5k indexed citations. Recurring topics across this work include Telemedicine and Telehealth Implementation (8 papers), Alzheimer's disease research and treatments (4 papers), Electronic Health Records Systems (3 papers), Dementia and Cognitive Impairment Research (3 papers), Healthcare Policy and Management (2 papers), Genetic Associations and Epidemiology (2 papers), Genomics and Chromatin Dynamics (1 paper) and Health Literacy and Information Accessibility (1 paper). The work is most often cited by research in Physiology (1.2k citations), Psychiatry and Mental health (773 citations), Neurology (258 citations), Health Informatics (51 citations) and Genetics (438 citations). Mitchell Tang has collaborated with scholars based in United States, Germany and France. Frequent co-authors include Ateev Mehrotra, Robert S. Huckman, A Jay Holmgren, Christopher Sharp, Chris Longhurst, Norman Lance Downing, Ariel Dora Stern, Christopher D. Brown, Lori Uscher‐Pines and Li‐San Wang. Their work appears in journals such as Health Affairs, JAMA Network Open, Journal of Alzheimer s Disease, Journal of General Internal Medicine and Nature Genetics.

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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