Emrah Irmak

737 citations
14 papers · 475 indexed · 1 hit paper · h-index 9
Topics
COVID-19 diagnosis using AI (5 papers)Brain Tumor Detection and Classification (4 papers)Radiomics and Machine Learning in Medical Imaging (2 papers)

In The Last Decade

Emrah Irmak

10 papers receiving 451 citations

Hit Papers

Multi-Classification of Brain Tumor MRI Images Using Deep...2021202620222024202150100150200250

Peers

Emrah Irmak
Comparison fields: 5 of 68
  • Neurology 256
  • Computer Vision and Pattern Recognition 251
  • Radiology, Nuclear Medicine and Imaging 196
  • Artificial Intelligence 186
  • Biomedical Engineering 41
Replace Saif Ur Rehman Khan with:
Saif Ur Rehman Khan China
Zaka Ur Rehman Malaysia
Kaleem Arshid China
Antônio Carlos da Silva Barros Brazil
Mohammad Amzad Hossain Bangladesh
Yehualashet Megersa Ayano Ethiopia
Ahmed S. Elkorany Egypt
Muhammad Sharif Pakistan
Tarun Agrawal India
Arnab Kumar Mishra India
Emrah Irmak relative to Saif Ur Rehman Khan China Saif Ur Rehman Khan's profile →
Citations per field
00.5×10×20×30×36.7×
Saif Ur Rehman Khan · 1×
Citations per year

Countries citing papers authored by Emrah Irmak

Since Specialization
Citations

This map shows the geographic impact of Emrah Irmak'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 Emrah Irmak with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Emrah Irmak more than expected).

Fields of papers citing papers by Emrah Irmak

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Emrah Irmak. 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 Emrah Irmak. The network helps show where Emrah Irmak may publish in the future.

Co-authorship network of co-authors of Emrah Irmak

This figure shows the co-authorship network connecting the top 25 collaborators of Emrah Irmak. A scholar is included among the top collaborators of Emrah Irmak based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Emrah Irmak. Emrah Irmak is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

14 of 14 papers shown
#WorkIndexed citations
1 0
2 1
3 23
4 0
5 22
6
Multi-Classification of Brain Tumor MRI Images Using Deep Convolutional Neural Network with Fully Optimized Frameworkbreakdown →
281
7 49
8 32
9 0
10 23
11 13
12 0
13 12
14 19

About Emrah Irmak

Emrah Irmak is a scholar working on Neurology, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging, having authored 14 papers that have together received 475 indexed citations. Recurring topics across this work include COVID-19 diagnosis using AI (5 papers), Brain Tumor Detection and Classification (4 papers) and Radiomics and Machine Learning in Medical Imaging (2 papers). The work is most often cited by research in Neurology (256 citations), Health Informatics (22 citations) and Computer Vision and Pattern Recognition (251 citations). Emrah Irmak has collaborated with scholars based in Türkiye, United Kingdom and United States. Frequent co-authors include Ahmet H. Ertas, Mehmet Bozdal, Ergun Erçelebi, Emrullah Acar, Musa Yılmaz and Ömer Türk. Their work appears in journals such as Physiological Genomics, Technology in Cancer Research & Treatment and IET Image Processing.

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.

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