Mehmet Gönen

6.1k citations
91 papers · 3.2k indexed · 1 hit paper · h-index 26
Topics
Gene expression and cancer classification (16 papers)Face and Expression Recognition (12 papers)Machine Learning in Bioinformatics (9 papers)

In The Last Decade

Mehmet Gönen

89 papers receiving 3.2k citations

Hit Papers

Multiple Kernel Learning Algorithms201120262016202120112505007501000

Peers

Mehmet Gönen
Comparison fields: 5 of 181
  • Artificial Intelligence 924
  • Computer Vision and Pattern Recognition 902
  • Molecular Biology 843
  • Computational Theory and Mathematics 501
  • Infectious Diseases 219
Replace Alan Wee‐Chung Liew with:
Alan Wee‐Chung Liew Australia
Changcheng Li China
Changming Sun Australia
Xiaotong Shen United States
Shulin Wang China
Christopher Tong United States
Chee Keong Kwoh Singapore
Yanda Li China
Pei Zhang China
Mehmet Gönen relative to Alan Wee‐Chung Liew Australia Alan Wee‐Chung Liew's profile →
Citations per field
00.5×6.4×
Alan Wee‐Chung Liew · 1×
Citations per year

Countries citing papers authored by Mehmet Gönen

Since Specialization
Citations

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

Fields of papers citing papers by Mehmet Gönen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mehmet Gönen

This figure shows the co-authorship network connecting the top 25 collaborators of Mehmet Gönen. A scholar is included among the top collaborators of Mehmet Gönen 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 Mehmet Gönen. Mehmet Gönen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 1
2 4
3 1
4 1
5 1
6 2
7 16
8 8
9 16
10
Automated Diagnosis of Keratoconus from Corneal Topography
1
11 5
12 10
13 6
14 10
15 46
16 9
17 28
18 16
19
Localized Data Fusion for Kernel k-Means Clustering with Application to Cancer Biology
108
20
Multiple Kernel Learning Algorithmsbreakdown →
1156

About Mehmet Gönen

Mehmet Gönen is a scholar working on Molecular Medicine, Endocrinology and Computer Vision and Pattern Recognition, having authored 91 papers that have together received 3.2k indexed citations. Recurring topics across this work include Gene expression and cancer classification (16 papers), Face and Expression Recognition (12 papers) and Machine Learning in Bioinformatics (9 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (902 citations), Computational Theory and Mathematics (501 citations) and Artificial Intelligence (924 citations). Mehmet Gönen has collaborated with scholars based in Türkiye, United States and Finland. Frequent co-authors include Ethem Alpaydın, Adam A. Margolin, Önder Ergönül, Samuel Kaski, Semra Ülkü, Devri̇m Balköse, Ram B. Gupta, Füsun Can, Emmanuel Nyankson and Fikret İnal. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nature Communications and SHILAP Revista de lepidopterología.

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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