M. Subramoniam

840 citations
35 papers · 549 · 1 hit paper · h-index 11

Impact in

Papers in

M. Subramoniam

31 papers receiving 534 citations

M. Subramoniam's Hit Papers

A Review of Machine Learning Algorithms for Biomedical Applications 2024 · 46 citations
460+1Years since publication10203040

Peers

M. Subramoniam
Comparison fields: 5 of 100
  • Insect Science 83
  • Biomedical Engineering 287
  • Health Information Management 30
  • Bioengineering 36
  • Sensory Systems 21
Replace Selda Güney with:
Selda Güney Türkiye
Marie-Louise O’Connell Ireland
Xue Jiang China
Georgios Stavropoulos Greece
Thomas Roddelkopf Germany
G. M. Naik India
G. Geetharamani India
Peng Wan China
Ashish Issac India
Mehmood Nawaz Hong Kong
M. Subramoniam relative to Selda Güney Türkiye Selda Güney's profile →
Citations per field
00.5×
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 8 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 202189
2 202170
3 202158
4 202152
5
A Review of Machine Learning Algorithms for Biomedical Applications
Hit paper breakdown →
202446
6 201842
7 202139
8 201818
9 202418
10 202116
11 202111
12 202310
13 202010
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 20134
20 20224

About M. Subramoniam

M. Subramoniam is a scholar working on Biomedical Engineering, Electrical and Electronic Engineering, Computer Vision and Pattern Recognition, Insect Science and Signal Processing, having authored 35 papers that have together received 549 indexed citations. Recurring topics across this work include Advanced Chemical Sensor Technologies (13 papers), Gas Sensing Nanomaterials and Sensors (12 papers), Insect Pheromone Research and Control (7 papers), Biometric Identification and Security (4 papers), AI in cancer detection (4 papers), IoT-based Smart Home Systems (3 papers), Digital Imaging for Blood Diseases (3 papers) and Face recognition and analysis (3 papers). The work is most often cited by research in Insect Science (83 citations), Biomedical Engineering (287 citations), Health Information Management (30 citations), Bioengineering (36 citations) and Sensory Systems (21 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, S. Naveen, J. Arun, V. Rajini, Ajay Kumar and Immanuel Rajkumar. Their work appears in journals such as Computers & Electrical Engineering, Microchemical Journal, Heritage Science, Soft Computing and Microsystem Technologies.

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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