S. Padmapriya

598 citations
38 papers · 325 · h-index 11

Impact in

    • Artificial Intelligence in Healthcare and Education
  • Neurology top 10%
    • Brain Tumor Detection and Classification

Papers in

S. Padmapriya

36 papers receiving 301 citations

Peers

S. Padmapriya
Comparison fields: 5 of 88
  • Health Informatics 19
  • Neurology 97
  • Computer Vision and Pattern Recognition 106
  • Radiology, Nuclear Medicine and Imaging 59
  • Health Information Management 12
Replace Md Mahbubur Rahman with:
Md Mahbubur Rahman Bangladesh
Chandradeep Bhatt India
Haytham Al-Feel Egypt
Antônio Carlos da Silva Barros Brazil
Harold Brayan Arteaga-Arteaga Colombia
Noha Negm Saudi Arabia
Ferhat Bozkurt Türkiye
Pawan Kumar Mall India
Hossein Kashiani United States
Soroush Baseri Saadi Belgium
S. Padmapriya relative to Md Mahbubur Rahman Bangladesh Md Mahbubur Rahman's profile →
Citations per field
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Md Mahbubur Rahman · 1×
Citations per year

Countries citing papers authored by S. Padmapriya

Since Specialization
Citations

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

Fields of papers citing papers by S. Padmapriya

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 13 scholars most cited alongside S. Padmapriya, 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 S. Padmapriya Line = papers co-authored together S. Padmapriya links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 38 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202062
2 202452
3 202021
4 202020
5 201218
6 202114
7 202113
8 202312
9 202212
10 201911
11 202211
12 20248
13 20147
14 20157
15 20226
16 20055
17 20165
18 20244
19 20194
20 20214

About S. Padmapriya

S. Padmapriya is a scholar working on Computer Vision and Pattern Recognition, Neurology, Artificial Intelligence, Electrical and Electronic Engineering and Computer Networks and Communications, having authored 38 papers that have together received 325 indexed citations. Recurring topics across this work include Brain Tumor Detection and Classification (12 papers), Advanced Neural Network Applications (7 papers), Advanced MIMO Systems Optimization (4 papers), Wireless Communication Networks Research (3 papers), Medical Image Segmentation Techniques (2 papers), Face and Expression Recognition (2 papers), Artificial Intelligence in Healthcare (2 papers) and Digital Filter Design and Implementation (2 papers). The work is most often cited by research in Health Informatics (19 citations), Neurology (97 citations), Computer Vision and Pattern Recognition (106 citations), Radiology, Nuclear Medicine and Imaging (59 citations) and Health Information Management (12 citations). S. Padmapriya has collaborated with scholars based in India, Malaysia and China. Frequent co-authors include P. Sriramakrishnan, S. Parthasarathy, K. Somasundaram, T. Kalaiselvi, N. Sri Madhava Raja, S. Gomathi, Ana Fred, N. Shanthi, Krishnan Nallaperumal and E. Kirubakaran. Their work appears in journals such as PeerJ Computer Science, International Journal of Dynamical Systems and Differential Equations, International Journal of Imaging Systems and Technology, Multimedia Tools and Applications and Engineering Science and Technology an International Journal.

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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