N. Arunkumar
Impact in
- Cognitive Neuroscience top 1%
- EEG and Brain-Computer Interfaces
- Neurology top 2%
- Brain Tumor Detection and Classification
- Parkinson's Disease Mechanisms and Treatments
Papers in
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- EEG and Brain-Computer Interfaces 27
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- Advanced DC-DC Converters 5
- Co-authors
- Gustavo Ramírez-González (15 shared papers)Enas Abdulhay (21 shared papers)Mazin Abed Mohammed (8 shared papers)U. Rajendra Acharya (14 shared papers)Mohd Khanapi Abd Ghani (6 shared papers)Shu Lih Oh (5 shared papers)Yuki Hagiwara (2 shared papers)Victor Hugo C. de Albuquerque (5 shared papers)
- Journals
- Future Generation Computer Systems (13 papers)IEEE Access (11 papers)International Journal of Heavy Vehicle Systems (4 papers)Cognitive Systems Research (4 papers)Computers & Electrical Engineering (4 papers)
- Partner nations
- IndiaUnited StatesJordan
In The Last Decade
N. Arunkumar
102 papers receiving 4.8k citations
N. Arunkumar's Hit Papers
Peers
Comparison fields: 5 of 180
- Cognitive Neuroscience 1.2k
- Neurology 459
- Urban Studies 310
- Signal Processing 488
- Computer Vision and Pattern Recognition 926
Countries citing papers authored by N. Arunkumar
This map shows the geographic impact of N. Arunkumar'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 N. Arunkumar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites N. Arunkumar more than expected).
Fields of papers citing papers by N. Arunkumar
This network shows the impact of papers produced by N. Arunkumar. 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 N. Arunkumar. The network helps show where N. Arunkumar may publish in the future.
Co-authors
The 25 scholars most cited alongside N. Arunkumar, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 108 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | A deep learning approach for Parkinson’s disease diagnosis from EEG signals Hit paper breakdown → | 2018 | 431 |
| 2 | Enabling technologies for fog computing in healthcare IoT systems Hit paper breakdown → | 2018 | 393 |
| 3 | Optimal deep learning model for classification of lung cancer on CT images Hit paper breakdown → | 2018 | 358 |
| 4 | Secure Medical Data Transmission Model for IoT-Based Healthcare Systems Hit paper breakdown → | 2018 | 314 |
| 5 | 2018 | 194 | |
| 6 | 2018 | 182 | |
| 7 | 2018 | 178 | |
| 8 | 2019 | 162 | |
| 9 | 2017 | 153 | |
| 10 | 2018 | 131 | |
| 11 | 2018 | 125 | |
| 12 | 2018 | 120 | |
| 13 | 2018 | 118 | |
| 14 | 2018 | 112 | |
| 15 | 2021 | 109 | |
| 16 | 2018 | 84 | |
| 17 | 2017 | 83 | |
| 18 | 2017 | 72 | |
| 19 | 2019 | 69 | |
| 20 | 2020 | 68 |
About N. Arunkumar
N. Arunkumar is a scholar working on Cognitive Neuroscience, Electrical and Electronic Engineering, Cardiology and Cardiovascular Medicine, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 108 papers that have together received 5.0k indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (27 papers), Brain Tumor Detection and Classification (8 papers), ECG Monitoring and Analysis (8 papers), Blind Source Separation Techniques (6 papers), Fractal and DNA sequence analysis (6 papers), Drug Solubulity and Delivery Systems (5 papers), Neural Networks and Applications (5 papers) and Advanced DC-DC Converters (5 papers). The work is most often cited by research in Cognitive Neuroscience (1.2k citations), Neurology (459 citations), Urban Studies (310 citations), Signal Processing (488 citations) and Computer Vision and Pattern Recognition (926 citations). N. Arunkumar has collaborated with scholars based in India, United States and Jordan. Frequent co-authors include Gustavo Ramírez-González, Enas Abdulhay, Mazin Abed Mohammed, U. Rajendra Acharya, Mohd Khanapi Abd Ghani, Shu Lih Oh, Yuki Hagiwara, Victor Hugo C. de Albuquerque, K. Shankar and Othman Mohd. Their work appears in journals such as Future Generation Computer Systems, IEEE Access, International Journal of Heavy Vehicle Systems, Cognitive Systems Research and Computers & Electrical Engineering.
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.