C. Gunavathi

490 citations
32 papers · 335 · h-index 10

Impact in

Papers in

    • Gene expression and cancer classification 9
    • Machine Learning in Bioinformatics 8
    • Protein Structure and Dynamics 3
    • AI in cancer detection 9
    • Machine Learning and Data Classification 4

C. Gunavathi

27 papers receiving 298 citations

Peers

C. Gunavathi
Comparison fields: 5 of 93
  • Health Informatics 6
  • Health Information Management 17
  • Artificial Intelligence 122
  • Radiology, Nuclear Medicine and Imaging 42
  • Information Systems 44
Replace Faris Kateb with:
Faris Kateb Saudi Arabia
Xuequn Shang China
Madhu Goyal Australia
Navneet Kumar Verma India
Santos Kumar Baliarsingh India
Haixia Long China
Zuhaira Muhammad Zain Saudi Arabia
Sanjay Nair India
Murtada K. Elbashir Saudi Arabia
Godwin Brown Tunze Tanzania
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Citations per field
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Citations per year

Countries citing papers authored by C. Gunavathi

Since Specialization
Citations

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

Fields of papers citing papers by C. Gunavathi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 11 scholars most cited alongside C. Gunavathi, 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 C. Gunavathi Line = papers co-authored together C. Gunavathi links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202247
2 201442
3 201436
4 201535
5 202026
6 202224
7 202318
8 201817
9 201916
10 202310
11 20219
12
3D reconstruction of a scene from multiple 2D images
20178
13 20177
14 20246
15 20186
16 20245
17
Classification of Microarray Data Based OnFeature Selection Method
20144
18 20184
19 20203
20 20242

About C. Gunavathi

C. Gunavathi is a scholar working on Molecular Biology, Artificial Intelligence, Information Systems, Health Information Management and Computational Theory and Mathematics, having authored 32 papers that have together received 335 indexed citations. Recurring topics across this work include Gene expression and cancer classification (9 papers), AI in cancer detection (9 papers), Machine Learning in Bioinformatics (8 papers), Machine Learning and Data Classification (4 papers), Brain Tumor Detection and Classification (3 papers), Data Mining Algorithms and Applications (3 papers), Protein Structure and Dynamics (3 papers) and Artificial Intelligence in Healthcare (3 papers). The work is most often cited by research in Health Informatics (6 citations), Health Information Management (17 citations), Artificial Intelligence (122 citations), Radiology, Nuclear Medicine and Imaging (42 citations) and Information Systems (44 citations). C. Gunavathi has collaborated with scholars based in India. Frequent co-authors include K. Sivasubramanian, P. Keerthika, P. Suresh, P. Pabitha, P. Venkatesh, Xiao Gao, C. Lavanya, Ramesh Chand Meena, Srinivas Koppu and K. Premalatha. Their work appears in journals such as IEEE Access, Progress in Biophysics and Molecular Biology, Chaos Solitons & Fractals, BioMolecular Concepts and BMC Medical Informatics and Decision Making.

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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