Godwin Brown Tunze
- Artificial Intelligence top 10%
- Wireless Signal Modulation Classification 3
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- Artificial Intelligence in Healthcare 2
- Information Systems top 10%
- Spam and Phishing Detection 1
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- Complex Network Analysis Techniques 2
- Opinion Dynamics and Social Influence 2
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- IoT and Edge/Fog Computing 1
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- Online Learning and Analytics 1
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- Misinformation and Its Impacts 1
- Co-authors
- Jae‐Min LeeDong‐Seong KimMounir HamdiThien Huynh‐TheM. PoongodiSarita SimaiyaV. VijayakumarAmandeep Kaur
- Journals
- IEEE Transactions on Vehicular Technology (1 paper)Computational and Mathematical Methods in Medicine (1 paper)International Journal of Information Technology and Web Engineering (4 papers)
In The Last Decade
Godwin Brown Tunze
8 papers receiving 281 citations
Hit Papers
Peers
Comparison fields: 5 of 95
- Artificial Intelligence 139
- Health Information Management 12
- Health Informatics 3
- Information Systems 47
- Computer Vision and Pattern Recognition 42
Countries citing papers authored by Godwin Brown Tunze
This map shows the geographic impact of Godwin Brown Tunze'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 Godwin Brown Tunze with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Godwin Brown Tunze more than expected).
Fields of papers citing papers by Godwin Brown Tunze
This network shows the impact of papers produced by Godwin Brown Tunze. 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 Godwin Brown Tunze. The network helps show where Godwin Brown Tunze may publish in the future.
Co-authorship network
The 19 scholars most cited alongside Godwin Brown Tunze, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 8 | |
| 2 | 2022 | 23 | |
| 3 | 2022 | 17 | |
| 4 | Hybrid Model for Detection of Cervical Cancer Using Causal Analysis and Machine Learning Techniquesbreakdown → | 2022 | 124 |
| 5 | 2022 | 21 | |
| 6 | 2020 | 3 | |
| 7 | 2020 | 26 | |
| 8 | 2020 | 72 |
About Godwin Brown Tunze
Godwin Brown Tunze is a scholar working on Health Information Management, Computer Science Applications and Statistical and Nonlinear Physics, having authored 8 papers that have together received 294 indexed citations. Recurring topics across this work include Wireless Signal Modulation Classification (3 papers), Artificial Intelligence in Healthcare (2 papers), Complex Network Analysis Techniques (2 papers), Opinion Dynamics and Social Influence (2 papers), IoT and Edge/Fog Computing (1 paper), Online Learning and Analytics (1 paper), Spam and Phishing Detection (1 paper) and Misinformation and Its Impacts (1 paper). The work is most often cited by research in Artificial Intelligence (139 citations), Health Information Management (12 citations) and Health Informatics (3 citations). Godwin Brown Tunze has collaborated with scholars based in Tanzania, India and Qatar. Frequent co-authors include Jae‐Min Lee, Dong‐Seong Kim, Mounir Hamdi, Thien Huynh‐The, M. Poongodi, Sarita Simaiya, V. Vijayakumar, Amandeep Kaur, Abeer D. Algarni and Umesh Kumar Lilhore. Their work appears in journals such as IEEE Transactions on Vehicular Technology, Computational and Mathematical Methods in Medicine and International Journal of Information Technology and Web 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.