V. Ramalingam

2.6k citations
65 papers · 1.7k indexed · 1 hit paper · h-index 21

Impact in

Papers in

V. Ramalingam

60 papers receiving 1.5k citations

Hit Papers

Heart disease prediction using machine learning techniques : a survey 2018 · 199 citations
199201820262020202350100150

Peers

V. Ramalingam
Comparison fields: 5 of 128
  • Computer Science Applications 498
  • Health Information Management 204
  • Signal Processing 294
  • Medical Laboratory Technology 35
  • Artificial Intelligence 629
Replace Nazik Alturki with:
Nazik Alturki Saudi Arabia
Roberto Muñoz Chile
Georgios Evangelidis Greece
Mihaela Cocea United Kingdom
Mona Jamjoom Saudi Arabia
Yutaka Watanobe Japan
Aaron Striegel United States
Santiago Ontañón United States
Michel C. Desmarais Canada
Lawrence Cavedon Australia
V. Ramalingam relative to Nazik Alturki Saudi Arabia Nazik Alturki's profile →
Citations per field
00.5×10×15×20×23.8×
Nazik Alturki · 1×
Citations per year

Countries citing papers authored by V. Ramalingam

Since Specialization
Citations

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

Fields of papers citing papers by V. Ramalingam

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20251
2 20250
3 20231
4 20230
5
PREDICTION OF LIVER DISEASE USING ARTIFICIALNEURAL NETWORK WITH ADAM OPTIMIZER
20202
6 20203
7 20181
8 20181
9 20160
10 20161
11 201639
12 20162
13 20153
14 20122
15
ANALYSIS OF EEG SIGNALS USING DATA MINING APPROACH
20121
16
Audio-Video Based Classification Using SVM
20111
17 201120
18 201062
19 20101
20 200981

About V. Ramalingam

V. Ramalingam is a scholar working on Signal Processing, Computer Science Applications, Computer Vision and Pattern Recognition, Artificial Intelligence and Health Information Management, having authored 65 papers that have together received 1.7k indexed citations. Recurring topics across this work include Music and Audio Processing (11 papers), Speech and Audio Processing (10 papers), Face and Expression Recognition (7 papers), Speech Recognition and Synthesis (7 papers), Teaching and Learning Programming (6 papers), Video Analysis and Summarization (5 papers), EEG and Brain-Computer Interfaces (5 papers) and Advanced Image Fusion Techniques (4 papers). The work is most often cited by research in Computer Science Applications (498 citations), Health Information Management (204 citations), Signal Processing (294 citations), Medical Laboratory Technology (35 citations) and Artificial Intelligence (629 citations). V. Ramalingam has collaborated with scholars based in India, United States and Saudi Arabia. Frequent co-authors include Susan Wiedenbeck, S. Palanivel, Deborah LaBelle, P. Dhanalakshmi, T. S. Subashini, S. Jothilakshmi, P. Bagavathi Sivakumar, Suseela T. Sarasamma, M. Balasubramanian and B. Amutha. Their work appears in journals such as Expert Systems with Applications, Indian Journal of Science and Technology, Engineering Applications of Artificial Intelligence, AI & Society and International Journal of Human-Computer Studies.

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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2026