M. Subramoniam

903 citations
35 papers · 600 · 1 hit paper · h-index 11

Impact in

Papers in

M. Subramoniam

32 papers receiving 589 citations

M. Subramoniam's Hit Papers

A Review of Machine Learning Algorithms for Biomedical Applications 2024 · 58 citations
580+1Years since publication1020304050

Peers

M. Subramoniam
Comparison fields: 5 of 103
  • Biomedical Engineering 311
  • Bioengineering 39
  • Health Information Management 28
  • Insect Science 70
  • Sensory Systems 19
Replace Selda Güney with:
Selda Güney Türkiye
Xitian Pi China
Junyu Zhang China
Haixia Yan China
Najam Ul Hasan South Korea
Vaegae Naveen Kumar India
Mohammad Ali Bagheri Canada
Muhammad Ali Akbar Qatar
Jessie R. Balbin Philippines
M. Subramoniam relative to Selda Güney Türkiye Selda Güney's profile →
Citations per field
00.5×3.4×
Selda Güney · 1×
Citations per year

Countries citing papers authored by M. Subramoniam

Since Specialization
Citations

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

Fields of papers citing papers by M. Subramoniam

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 7 scholars most cited alongside M. Subramoniam, 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. Subramoniam Line = papers co-authored together M. Subramoniam links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202197
2 202177
3 202163
4 202159
5
A Review of Machine Learning Algorithms for Biomedical Applications
Hit paper breakdown →
202458
6 201842
7 202140
8 202421
9 202118
10 201818
11 202112
12 202010
13 202310
14
MOS Based Sensor Array System for the Detection of Human Breath Volatile Organic Compounds
20219
15 20229
16
A non-invasive computer aided diagnosis of osteoarthritis from digitalx-ray images
20157
17 20197
18 20227
19 20245
20 20224

About M. Subramoniam

M. Subramoniam is a scholar working on Biomedical Engineering, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering, Signal Processing and Artificial Intelligence, having authored 35 papers that have together received 600 indexed citations. Recurring topics across this work include Advanced Chemical Sensor Technologies (13 papers), Gas Sensing Nanomaterials and Sensors (9 papers), Biometric Identification and Security (4 papers), AI in cancer detection (4 papers), Insect Pheromone Research and Control (4 papers), Digital Imaging for Blood Diseases (3 papers), Face recognition and analysis (3 papers) and Image and Signal Denoising Methods (3 papers). The work is most often cited by research in Biomedical Engineering (311 citations), Bioengineering (39 citations), Health Information Management (28 citations), Insect Science (70 citations) and Sensory Systems (19 citations). M. Subramoniam has collaborated with scholars based in India and United Arab Emirates. Frequent co-authors include V A Binson, Luke Mathew, S. Madhu, J. Arun, V. Rajini, Ajay Kumar and Immanuel Rajkumar. Their work appears in journals such as Computers & Electrical Engineering, Microchemical Journal, Multimedia Tools and Applications, IEEE Sensors Journal and Applied Computing and Informatics.

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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