N. Arunkumar
Impact in
- Health Information Management top 0.5%
- Artificial Intelligence in Healthcare
- Cognitive Neuroscience top 2%
- EEG and Brain-Computer Interfaces
Papers in
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- EEG and Brain-Computer Interfaces 28
- Autism Spectrum Disorder Research 7
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- Artificial Intelligence in Healthcare 9
- Co-authors
- Gustavo Ramírez-González (17 shared papers)Enas Abdulhay (22 shared papers)Mazin Abed Mohammed (9 shared papers)U Rajendra Acharya (14 shared papers)Mohd Khanapi Abd Ghani (6 shared papers)Shu Lih Oh (5 shared papers)Victor Hugo C. de Albuquerque (9 shared papers)K. Shankar (2 shared papers)
In The Last Decade
N. Arunkumar
88 papers receiving 5.4k citations
N. Arunkumar's Hit Papers
Peers
Comparison fields: 5 of 142
- Health Information Management 516
- Cognitive Neuroscience 1.1k
- Health Informatics 76
- Computer Vision and Pattern Recognition 712
- Neurology 226
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 89 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 | 496 |
| 2 | Enabling technologies for fog computing in healthcare IoT systems Hit paper breakdown → | 2018 | 462 |
| 3 | Optimal deep learning model for classification of lung cancer on CT images Hit paper breakdown → | 2018 | 425 |
| 4 | 2018 | 398 | |
| 5 | 2018 | 225 | |
| 6 | 2018 | 200 | |
| 7 | 2019 | 189 | |
| 8 | 2018 | 188 | |
| 9 | 2018 | 160 | |
| 10 | 2017 | 156 | |
| 11 | 2018 | 146 | |
| 12 | 2018 | 142 | |
| 13 | 2018 | 126 | |
| 14 | 2018 | 123 | |
| 15 | 2021 | 119 | |
| 16 | 2018 | 96 | |
| 17 | 2017 | 86 | |
| 18 | 2018 | 80 | |
| 19 | 2019 | 75 | |
| 20 | 2018 | 73 |
About N. Arunkumar
N. Arunkumar is a scholar working on Cognitive Neuroscience, Health Information Management, Computer Vision and Pattern Recognition, Biomedical Engineering and Neurology, having authored 89 papers that have together received 5.6k indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (28 papers), Artificial Intelligence in Healthcare (9 papers), Autism Spectrum Disorder Research (7 papers), Non-Invasive Vital Sign Monitoring (7 papers), AI in cancer detection (5 papers), Brain Tumor Detection and Classification (3 papers), Traditional Chinese Medicine Studies (3 papers) and ECG Monitoring and Analysis (3 papers). The work is most often cited by research in Health Information Management (516 citations), Cognitive Neuroscience (1.1k citations), Health Informatics (76 citations), Computer Vision and Pattern Recognition (712 citations) and Neurology (226 citations). N. Arunkumar has collaborated with scholars based in India, Jordan and Colombia. Frequent co-authors include Gustavo Ramírez-González, Enas Abdulhay, Mazin Abed Mohammed, U Rajendra Acharya, Mohd Khanapi Abd Ghani, Shu Lih Oh, Victor Hugo C. de Albuquerque, K. Shankar, S. K. Lakshmanaprabu and Ammar Awad Mutlag. Their work appears in journals such as Future Generation Computer Systems, IEEE Access, Computers & Electrical Engineering, Cognitive Systems Research and International Journal of Heavy Vehicle Systems.
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.