Swamy Laxminarayan

28 papers receiving 895 citations

Peers

Swamy Laxminarayan
Comparison fields: 5 of 130
  • Cognitive Neuroscience 285
  • Cardiology and Cardiovascular Medicine 187
  • Computer Vision and Pattern Recognition 176
  • Radiology, Nuclear Medicine and Imaging 162
  • Biomedical Engineering 141
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Citations per field
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Citations per year

Countries citing papers authored by Swamy Laxminarayan

Since Specialization
Citations

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

Fields of papers citing papers by Swamy Laxminarayan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Swamy Laxminarayan

This figure shows the co-authorship network connecting the top 25 collaborators of Swamy Laxminarayan. A scholar is included among the top collaborators of Swamy Laxminarayan based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Swamy Laxminarayan. Swamy Laxminarayan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 1
2 0
3 0
4 25
5 96
6 203
7
Handbook of Biomedical Image Analysis: Volume 3: Registration Models (International Topics in Biomedical Engineering)
13
8
Handbook of Biomedical Image Analysis: Volume 1: Segmentation Models Part A (Topics in Biomedical EngineeringInternational Book Series)
7
9 310
10 15
11
Plaque imaging using ultrasound, magnetic resonance and computer tomography: a review.
2
12 22
13
Economic impact of telemedicine: a survey.
7
14 65
15
Information technology and behavioral medicine: impact on autism treatment & research.
4
16 15
17 4
18 21
19 1
20 3

About Swamy Laxminarayan

Swamy Laxminarayan is a scholar working on General Dentistry, Radiology, Nuclear Medicine and Imaging and Computer Vision and Pattern Recognition, having authored 33 papers that have together received 966 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (5 papers), Radiomics and Machine Learning in Medical Imaging (3 papers) and Cardiovascular Health and Disease Prevention (3 papers). The work is most often cited by research in Cognitive Neuroscience (285 citations), Signal Processing (93 citations) and Computer Vision and Pattern Recognition (176 citations). Swamy Laxminarayan has collaborated with scholars based in United States, Netherlands and Singapore. Frequent co-authors include Jasjit S. Suri, U. Rajendra Acharya, N. Kannathal, Constantinos S. Pattichis, R.S.H. Istepanian, Oliver Faust, David L. Wilson, Radhika Sivaramakrishna, Cheng‐Chang Lu and Nicolaas Westerhof. Their work appears in journals such as Annals of the New York Academy of Sciences, IEEE Transactions on Biomedical Engineering and SLEEP.

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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