Kokeb Dese
Impact in
- Health Informatics top 5%
- Artificial Intelligence in Healthcare and Education
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- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
Papers in
-
- AI in cancer detection 5
- Domain Adaptation and Few-Shot Learning 2
-
- Digital Imaging for Blood Diseases 2
- Co-authors
- Gelan Ayana (10 shared papers)Se‐woon Choe (4 shared papers)Timothy Kwa (4 shared papers)Janarthanan Krishnamoorthy (3 shared papers)Gizeaddis Lamesgin Simegn (3 shared papers)Wondimagegn Adissu (2 shared papers)Tilahun Yemane (1 shared paper)Soon‐Do Yoon (1 shared paper)
- Journals
- Cancers (1 paper)Infectious Disease Modelling (1 paper)BMC Pediatrics (1 paper)Scientific African (1 paper)HardwareX (1 paper)
- Partner nations
- EthiopiaSouth KoreaUnited States
In The Last Decade
Kokeb Dese
14 papers receiving 364 citations
Peers
Comparison fields: 5 of 87
- Health Informatics 29
- Radiology, Nuclear Medicine and Imaging 163
- Artificial Intelligence 208
- Computer Vision and Pattern Recognition 100
- Neurology 35
Countries citing papers authored by Kokeb Dese
This map shows the geographic impact of Kokeb Dese'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 Kokeb Dese with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kokeb Dese more than expected).
Fields of papers citing papers by Kokeb Dese
This network shows the impact of papers produced by Kokeb Dese. 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 Kokeb Dese. The network helps show where Kokeb Dese may publish in the future.
Co-authors
The 13 scholars most cited alongside Kokeb Dese, 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 | 2021 | 117 | |
| 2 | 2023 | 66 | |
| 3 | 2021 | 62 | |
| 4 | 2021 | 31 | |
| 5 | 2024 | 17 | |
| 6 | 2022 | 14 | |
| 7 | 2023 | 13 | |
| 8 | 2022 | 13 | |
| 9 | 2022 | 12 | |
| 10 | 2024 | 12 | |
| 11 | 2024 | 10 | |
| 12 | 2021 | 6 | |
| 13 | 2023 | 4 | |
| 14 | 2024 | 2 | |
| 15 | 2024 | 0 | |
| 16 | 2022 | 0 |
About Kokeb Dese
Kokeb Dese is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Oncology and Pediatrics, Perinatology and Child Health, having authored 16 papers that have together received 379 indexed citations. Recurring topics across this work include AI in cancer detection (5 papers), Cutaneous Melanoma Detection and Management (2 papers), COVID-19 diagnosis using AI (2 papers), Artificial Intelligence in Healthcare and Education (2 papers), Domain Adaptation and Few-Shot Learning (2 papers), Digital Imaging for Blood Diseases (2 papers), Ethics and Social Impacts of AI (2 papers) and Radiomics and Machine Learning in Medical Imaging (2 papers). The work is most often cited by research in Health Informatics (29 citations), Radiology, Nuclear Medicine and Imaging (163 citations), Artificial Intelligence (208 citations), Computer Vision and Pattern Recognition (100 citations) and Neurology (35 citations). Kokeb Dese has collaborated with scholars based in Ethiopia, South Korea and United States. Frequent co-authors include Gelan Ayana, Se‐woon Choe, Timothy Kwa, Janarthanan Krishnamoorthy, Gizeaddis Lamesgin Simegn, Wondimagegn Adissu, Tilahun Yemane, Soon‐Do Yoon, Jude Dzevela Kong and B. Mellado. Their work appears in journals such as Cancers, Infectious Disease Modelling, BMC Pediatrics, Scientific African and HardwareX.
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.