Emre Dandıl
Impact in
- Neurology top 10%
- Brain Tumor Detection and Classification
-
- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
Papers in
-
- AI in cancer detection 10
- 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)Arzu Canan (1 shared paper)Özlem Kar Kurt (1 shared paper)Metin Özkan (1 shared paper)Bülent Yılmaz (1 shared paper)Mevlüt Kurt (1 shared paper)Güray Can (1 shared paper)
- Journals
- IEEE Access (3 papers)Journal of Clinical Medicine (2 papers)Gazi Üniversitesi Mühendislik-Mimarlık Fakültesi Dergisi (2 papers)Veterinary Sciences (1 paper)Journal of Applied Biomedicine (1 paper)
- Partner nations
- TürkiyeCambodiaUnited States
In The Last Decade
Emre Dandıl
45 papers receiving 361 citations
Peers
Comparison fields: 5 of 86
- Neurology 69
- Radiology, Nuclear Medicine and Imaging 162
- Health Informatics 9
- Artificial Intelligence 144
- Computer Vision and Pattern Recognition 81
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 | 74 | |
| 2 | 2014 | 57 | |
| 3 | 2020 | 35 | |
| 4 | 2016 | 23 | |
| 5 | 2018 | 23 | |
| 6 | 2019 | 20 | |
| 7 | 2020 | 17 | |
| 8 | Real-time Facial Emotion Classification Using Deep Learning | 2019 | 15 |
| 9 | 2012 | 9 | |
| 10 | 2019 | 9 | |
| 11 | 2020 | 8 | |
| 12 | 2019 | 7 | |
| 13 | 2019 | 6 | |
| 14 | 2013 | 6 | |
| 15 | 2021 | 5 | |
| 16 | 2018 | 5 | |
| 17 | 2021 | 5 | |
| 18 | 2021 | 5 | |
| 19 | 2024 | 4 | |
| 20 | 2020 | 4 |
About Emre Dandıl
Emre Dandıl is a scholar working on Artificial Intelligence, Neurology, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Biomedical Engineering, having authored 54 papers that have together received 388 indexed citations. Recurring topics across this work include Brain Tumor Detection and Classification (15 papers), AI in cancer detection (10 papers), Radiomics and Machine Learning in Medical Imaging (8 papers), Medical Imaging and Analysis (6 papers), Digital Imaging for Blood Diseases (4 papers), Artificial Immune Systems Applications (4 papers), Anomaly Detection Techniques and Applications (4 papers) and Advanced MRI Techniques and Applications (3 papers). The work is most often cited by research in Neurology (69 citations), Radiology, Nuclear Medicine and Imaging (162 citations), Health Informatics (9 citations), Artificial Intelligence (144 citations) and Computer Vision and Pattern Recognition (81 citations). Emre Dandıl has collaborated with scholars based in Türkiye, Cambodia and United States. Frequent co-authors include Murat Çakıroğlu, Kerim Kürşat Çevi̇k, Arzu Canan, Özlem Kar Kurt, Metin Özkan, Bülent Yılmaz, Mevlüt Kurt, Güray Can, Uğur Korkmaz and Mustafa Boğa. Their work appears in journals such as IEEE Access, Journal of Clinical Medicine, Gazi Üniversitesi Mühendislik-Mimarlık Fakültesi Dergisi, Veterinary Sciences and Journal of Applied Biomedicine.
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.