Emre Dandıl
Impact in
- Neurology top 10%
- Brain Tumor Detection and Classification
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- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
Papers in
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- AI in cancer detection 9
- Anomaly Detection Techniques and Applications 4
- Neurology 15
- Brain Tumor Detection and Classification 15
- Co-authors
- Murat Çakıroğlu (6 shared papers)Kerim Kürşat Çevi̇k (6 shared papers)Özlem Kar Kurt (1 shared paper)Arzu Canan (1 shared paper)Bülent Yılmaz (1 shared paper)Mevlüt Kurt (1 shared paper)Güray Can (1 shared paper)Metin Özkan (1 shared paper)
In The Last Decade
Emre Dandıl
46 papers receiving 375 citations
Peers
Comparison fields: 5 of 86
- Neurology 65
- Radiology, Nuclear Medicine and Imaging 141
- Artificial Intelligence 133
- Computer Vision and Pattern Recognition 79
- Health Informatics 4
Countries citing papers authored by Emre Dandıl
This map shows the geographic impact of Emre Dandıl'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 Emre Dandıl with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Emre Dandıl more than expected).
Fields of papers citing papers by Emre Dandıl
This network shows the impact of papers produced by Emre Dandıl. 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 Emre Dandıl. The network helps show where Emre Dandıl may publish in the future.
Co-authors
The 18 scholars most cited alongside Emre Dandıl, 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 54 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 77 | |
| 2 | 2014 | 58 | |
| 3 | 2020 | 37 | |
| 4 | 2018 | 25 | |
| 5 | 2016 | 23 | |
| 6 | 2019 | 21 | |
| 7 | 2020 | 17 | |
| 8 | Real-time Facial Emotion Classification Using Deep Learning | 2019 | 15 |
| 9 | 2019 | 9 | |
| 10 | 2012 | 9 | |
| 11 | 2020 | 8 | |
| 12 | 2019 | 8 | |
| 13 | 2013 | 6 | |
| 14 | 2019 | 6 | |
| 15 | 2021 | 5 | |
| 16 | 2018 | 5 | |
| 17 | 2021 | 5 | |
| 18 | 2024 | 4 | |
| 19 | 2020 | 4 | |
| 20 | 2021 | 4 |
About Emre Dandıl
Emre Dandıl is a scholar working on Artificial Intelligence, Neurology, Computer Vision and Pattern Recognition, Biomedical Engineering and Radiology, Nuclear Medicine and Imaging, having authored 54 papers that have together received 403 indexed citations. Recurring topics across this work include Brain Tumor Detection and Classification (15 papers), AI in cancer detection (9 papers), Medical Imaging and Analysis (6 papers), Radiomics and Machine Learning in Medical Imaging (6 papers), Digital Imaging for Blood Diseases (4 papers), Anomaly Detection Techniques and Applications (4 papers), Artificial Immune Systems Applications (4 papers) and Advanced Neural Network Applications (3 papers). The work is most often cited by research in Neurology (65 citations), Radiology, Nuclear Medicine and Imaging (141 citations), Artificial Intelligence (133 citations), Computer Vision and Pattern Recognition (79 citations) and Health Informatics (4 citations). Emre Dandıl has collaborated with scholars based in Türkiye, Cambodia and Somalia. Frequent co-authors include Murat Çakıroğlu, Kerim Kürşat Çevi̇k, Özlem Kar Kurt, Arzu Canan, Bülent Yılmaz, Mevlüt Kurt, Güray Can, Metin Özkan, Uğur Korkmaz and Mehmet Korkmaz. Their work appears in journals such as IEEE Access, Gazi Üniversitesi Mühendislik-Mimarlık Fakültesi Dergisi, Journal of Clinical Medicine, Multimedia Tools and Applications and Data in Brief.
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.