Darwin Castillo

35 papers receiving 267 citations

Peers

Darwin Castillo
Comparison fields: 5 of 73
  • Neurology 25
  • Electronic, Optical and Magnetic Materials 51
  • Rheumatology 36
  • Periodontics 10
  • Radiology, Nuclear Medicine and Imaging 49
Replace Jiho Lee with:
Jiho Lee South Korea
Souvik Chakraborty United States
Lirui Wang China
Zilu Zhang China
Chenjian Wu China
Danqing Ma China
Darwin Castillo relative to Jiho Lee South Korea Jiho Lee's profile →
Citations per field
00.5×2×4×6×8.2×
Jiho Lee · 1×
Citations per year

Countries citing papers authored by Darwin Castillo

Since Specialization
Citations

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

Fields of papers citing papers by Darwin Castillo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 42 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202261
2 199753
3 202118
4 202215
5 201714
6 202413
7 200910
8 19938
9 19968
10 20247
11 20186
12 20146
13
Soft Mask for Via Patterning in Benzocyclobutene
19935
14 20185
15 20195
16 20215
17 20234
18 20174
19 20223
20 20193

About Darwin Castillo

Darwin Castillo is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Electrical and Electronic Engineering, Biomedical Engineering and Materials Chemistry, having authored 42 papers that have together received 279 indexed citations. Recurring topics across this work include AI in cancer detection (6 papers), Brain Tumor Detection and Classification (6 papers), Digital Imaging for Blood Diseases (4 papers), Radiomics and Machine Learning in Medical Imaging (4 papers), Gas Sensing Nanomaterials and Sensors (4 papers), TiO2 Photocatalysis and Solar Cells (3 papers), Osteoarthritis Treatment and Mechanisms (2 papers) and Medical Image Segmentation Techniques (2 papers). The work is most often cited by research in Neurology (25 citations), Electronic, Optical and Magnetic Materials (51 citations), Rheumatology (36 citations), Periodontics (10 citations) and Radiology, Nuclear Medicine and Imaging (49 citations). Darwin Castillo has collaborated with scholars based in Ecuador, Spain and Canada. Frequent co-authors include Vasudevan Lakshminarayanan, María José Rodríguez-Álvarez, Arvids Stashans, P. H. Townsend, Steve Martin, J. P. Godschalx, Dennis W. Smith, Edward O. Shaffer, R. C. DeVries and Nelson G. Rondan. Their work appears in journals such as Applied Sciences, Biosensors, Physica B Condensed Matter, Journal of Modern Optics and Polymers.

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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