Richard J. Maude

18.8k citations
172 papers · 4.4k indexed · 2 hit papers · h-index 34

Richard J. Maude

164 papers receiving 4.2k citations

Hit Papers

Pre-trained convolutional neural networks as feature extr...3292018202620202023100200300

Peers

Richard J. Maude
Comparison fields: 5 of 176
  • Parasitology 574
  • Public Health, Environmental and Occupational Health 2.5k
  • Computer Vision and Pattern Recognition 1.1k
  • Biophysics 268
  • Modeling and Simulation 199
Replace Kamolrat Silamut with:
Kamolrat Silamut Thailand
Andreas Mårtensson Sweden
David Bell Canada
Sanjay K. Jain United States
Danny A. Milner United States
Ming‐Chieh Lee United States
James E. Kirby United States
Jennifer L. Gardy Canada
Timothy William Malaysia
Richard J. Maude relative to Kamolrat Silamut Thailand Kamolrat Silamut's profile →
Citations per field
00.5×10×15×18.1×
Kamolrat Silamut · 1×
Citations per year

Countries citing papers authored by Richard J. Maude

Since Specialization
Citations

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

Fields of papers citing papers by Richard J. Maude

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Richard J. Maude. 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 Richard J. Maude. The network helps show where Richard J. Maude may publish in the future.

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20251
2 20241
3 20241
4 20248
5 20240
6 20243
7 20242
8 20243
9 20235
10 20236
11
Mapping genetic markers of artemisinin resistance in <i>Plasmodium falciparum</i> malaria in Asia: a systematic review and spatiotemporal analysis
202226
12 20221
13 202223
14 20217
15 20216
16 202122
17 201729
18 20141
19 2010116
20 200950

About Richard J. Maude

Richard J. Maude is a scholar working on Modeling and Simulation, Public Health, Environmental and Occupational Health and Parasitology, having authored 172 papers that have together received 4.4k indexed citations. Recurring topics across this work include Malaria Research and Control (91 papers), Mosquito-borne diseases and control (90 papers), COVID-19 epidemiological studies (19 papers), Digital Imaging for Blood Diseases (18 papers), Global Maternal and Child Health (15 papers), Viral Infections and Vectors (14 papers), Computational Drug Discovery Methods (14 papers) and Travel-related health issues (13 papers). The work is most often cited by research in Parasitology (574 citations), Public Health, Environmental and Occupational Health (2.5k citations) and Computer Vision and Pattern Recognition (1.1k citations). Richard J. Maude has collaborated with scholars based in Thailand, United Kingdom and United States. Frequent co-authors include Stefan Jaeger, Arjen M. Dondorp, Kamolrat Silamut, Mahdieh Poostchi, Nicholas J. White, George R. Thoma, Nicholas Day, Lisa J. White, Stuart D. Blacksell and Sameer Antani. Their work appears in journals such as Proceedings of the National Academy of Sciences, SHILAP Revista de lepidopterología and PLoS ONE.

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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