Matthew Smith

23 papers receiving 335 citations

Peers

Matthew Smith
Comparison fields: 5 of 96
  • Applied Microbiology and Biotechnology 12
  • Aquatic Science 30
  • Business and International Management 8
  • Emergency Medical Services 25
  • Architecture 5
Replace Mónica Chávez with:
Mónica Chávez Colombia
Shiva Bhandari United States
Yuesheng Li Australia
Cecilia Li Australia
José Rodrigo Santos Silva Brazil
Atiya Rahman Pakistan
Jasen Kunz United States
Carolyn Lewis South Africa
Shweta Sharma India
Meseret Girma Ethiopia
Matthew Smith relative to Mónica Chávez Colombia Mónica Chávez's profile →
Citations per field
00.5×6.3×
Mónica Chávez · 1×
Citations per year

Countries citing papers authored by Matthew Smith

Since Specialization
Citations

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

Fields of papers citing papers by Matthew Smith

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Induction of pro- and anti-inflammatory molecules in a mouse model of pneumococcal pneumonia after influenza.
2007105
2 201773
3 201768
4 202329
5 202411
6 20239
7 20239
8 20217
9 19946
10 20125
11
V-Series (Ve, Vg, Vm, Vx) Toxicity
20193
12 20243
13 20133
14 20092
15 20212
16 20222
17 20231
18 20221
19 20241
20 20231

About Matthew Smith

Matthew Smith is a scholar working on Infectious Diseases, Epidemiology, Public Health, Environmental and Occupational Health, General Health Professions and Emergency Medicine, having authored 24 papers that have together received 344 indexed citations. Recurring topics across this work include Antimicrobial Resistance in Staphylococcus (5 papers), Emergency and Acute Care Studies (3 papers), Antibiotic Use and Resistance (3 papers), Antibiotics Pharmacokinetics and Efficacy (2 papers), Bacterial Identification and Susceptibility Testing (2 papers), Disaster Response and Management (2 papers), Disaster Management and Resilience (2 papers) and Streptococcal Infections and Treatments (2 papers). The work is most often cited by research in Applied Microbiology and Biotechnology (12 citations), Aquatic Science (30 citations), Business and International Management (8 citations), Emergency Medical Services (25 citations) and Architecture (5 citations). Matthew Smith has collaborated with scholars based in United States and Australia. Frequent co-authors include Jonathan A. McCullers, Carlos J. Orihuela, Jeffrey E. Schmidt, Jerold E. Rehg, Philip W. Smith, Christopher J. Kratochvil, Shelly Schwedhelm, Jodi D. Sherman, Hardeep Singh and Samuel S. Myers. Their work appears in journals such as Infection Control and Hospital Epidemiology, Clinical Infectious Diseases, JAMA, JAMA Network Open and Journal of Engineering Education.

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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