M. Pavithra

58 papers receiving 306 citations

Peers

M. Pavithra
Comparison fields: 5 of 104
  • Health Information Management 14
  • Biomedical Engineering 108
  • Materials Chemistry 72
  • Geometry and Topology 11
  • Computer Vision and Pattern Recognition 25
Replace Vinay Kumar Singh with:
Vinay Kumar Singh India
Ji Hwan Park South Korea
Priti Gupta India
Xianchuan Wang China
Poonam Singh India
K. Geetha India
N. Arun Vignesh India
Siva Ananth Mariappan India
Neha Yadav India
M. Pavithra relative to Vinay Kumar Singh India Vinay Kumar Singh's profile →
Citations per field
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Citations per year

Countries citing papers authored by M. Pavithra

Since Specialization
Citations

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

Fields of papers citing papers by M. Pavithra

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 79 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201761
2 201843
3 201920
4 201819
5 201919
6 202012
7 202211
8 20208
9 20148
10 20218
11
Effective Heart Disease Prediction Systems Using Data Mining Techniques
20216
12 20216
13 20196
14 20225
15 20205
16 20195
17 20195
18 20215
19 20205
20
Nitrogen and sulphur nutrition for enhancing the growth and yield of quality protein maize (QPM)
20184

About M. Pavithra

M. Pavithra is a scholar working on Computer Vision and Pattern Recognition, Computational Theory and Mathematics, Geometry and Topology, Materials Chemistry and Electrical and Electronic Engineering, having authored 79 papers that have together received 332 indexed citations. Recurring topics across this work include Graph theory and applications (9 papers), Advanced Graph Theory Research (7 papers), Artificial Intelligence in Healthcare (6 papers), Metamaterials and Metasurfaces Applications (5 papers), Graph Labeling and Dimension Problems (5 papers), Advanced Antenna and Metasurface Technologies (4 papers), Antenna Design and Analysis (4 papers) and Advanced Clustering Algorithms Research (3 papers). The work is most often cited by research in Health Information Management (14 citations), Biomedical Engineering (108 citations), Materials Chemistry (72 citations), Geometry and Topology (11 citations) and Computer Vision and Pattern Recognition (25 citations). M. Pavithra has collaborated with scholars based in India, Saudi Arabia and United States. Frequent co-authors include S. Muruganand, N. D. Pradeep Singh, Dwaipayan Sen, L. Vinod Kumar Reddy, B. T. Geetha, K. Saruladha, T. Ananth Kumar, K. Ganesan, Bindu M. Kutty and K. Ravichandran. Their work appears in journals such as ACS Applied Nano Materials, Sensors and Actuators B Chemical, RSC Advances, Indian Journal of Science and Technology and Organic & Biomolecular Chemistry.

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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