S. Srividhya

763 citations
58 papers · 405 · 1 hit paper · h-index 8

Impact in

Papers in

S. Srividhya

48 papers receiving 369 citations

Hit Papers

Early-Stage Alzheimer's Disease Prediction Using Machine Learning Models 2022 · 170 citations
1700+1+2Years since publication50100150

Peers

S. Srividhya
Comparison fields: 5 of 84
  • Health Information Management 76
  • Neurology 89
  • Health Informatics 14
  • Artificial Intelligence 126
  • Psychiatry and Mental health 51
Replace Suriya Murugan with:
Suriya Murugan India
Modupe Odusami Lithuania
Ahmad Al Smadi China
Muhammad Nadeem Majeed Pakistan
Kazi Abu Taher Bangladesh
Umair Khan Pakistan
Vinodhini Mani India
Mohemmed Sha Saudi Arabia
Shukuan Lin China
Faten S. Alamri Saudi Arabia
S. Srividhya relative to Suriya Murugan India Suriya Murugan's profile →
Citations per field
00.5×
Suriya Murugan · 1×
Citations per year

Countries citing papers authored by S. Srividhya

Since Specialization
Citations

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

Fields of papers citing papers by S. Srividhya

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 58 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Early-Stage Alzheimer's Disease Prediction Using Machine Learning Models
Hit paper breakdown →
2022170
2 202227
3 202225
4 202224
5 202020
6 202215
7 201612
8 20229
9 20237
10 20167
11 20187
12 20226
13 20226
14 20215
15 20234
16 20184
17 20193
18 20223
19 20213
20 20183

About S. Srividhya

S. Srividhya is a scholar working on Computer Networks and Communications, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering, Information Systems and Artificial Intelligence, having authored 58 papers that have together received 405 indexed citations. Recurring topics across this work include IoT-based Smart Home Systems (6 papers), Energy Efficient Wireless Sensor Networks (4 papers), Brain Tumor Detection and Classification (4 papers), Advanced Neural Network Applications (3 papers), IoT and Edge/Fog Computing (3 papers), Video Surveillance and Tracking Methods (3 papers), Blockchain Technology Applications and Security (3 papers) and Retinal Imaging and Analysis (3 papers). The work is most often cited by research in Health Information Management (76 citations), Neurology (89 citations), Health Informatics (14 citations), Artificial Intelligence (126 citations) and Psychiatry and Mental health (51 citations). S. Srividhya has collaborated with scholars based in India, Taiwan and United States. Frequent co-authors include C. Kavitha, Vinodhini Mani, Osamah Ibrahim Khalaf, Carlos Andrés Tavera Romero, Suresh Sankaranarayanan, Sanjiv Jain, Wen‐Cheng Lai, Tao Hai, Md Habibur Rahman and Jincheng Zhou. Their work appears in journals such as Electronics, Frontiers in Public Health, Scientific Reports, Advances in Complex Systems and Indian Journal of Science and Technology.

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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