Cagri Ozcaglar

441 citations
15 papers · 299 indexed · h-index 6
Topics
Tuberculosis Research and Epidemiology (9 papers)Mycobacterium research and diagnosis (6 papers)Machine Learning in Bioinformatics (4 papers)
Partner nations
United StatesGuadeloupe

In The Last Decade

Cagri Ozcaglar

14 papers receiving 286 citations

Peers

Cagri Ozcaglar
Comparison fields: 5 of 81
  • Infectious Diseases 135
  • Epidemiology 120
  • Surgery 70
  • Artificial Intelligence 55
  • Molecular Biology 54
Replace Shiraz Gefen-Halevi with:
Shiraz Gefen-Halevi Israel
Cheuk‐Kwong Lee Hong Kong
Wudi Wei China
Liang Tian China
Chia‐Hung Liao Taiwan
Zhichao Liang China
Jingzhen Lai China
Anthony Huffman United States
Elizabeth Hunter Ireland
José Segovia-Juárez United States
Cagri Ozcaglar relative to Shiraz Gefen-Halevi Israel Shiraz Gefen-Halevi's profile →
Citations per field
00.5×11×
Shiraz Gefen-Halevi · 1×
Citations per year

Countries citing papers authored by Cagri Ozcaglar

Since Specialization
Citations

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

Fields of papers citing papers by Cagri Ozcaglar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Cagri Ozcaglar

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

All Works

15 of 15 papers shown
#WorkIndexed citations
1 44
2 22
3 3
4 4
5 80
6 3
7 74
8
Algorithmic data fusion methods for tuberculosis
1
9 1
10 28
11 31
12 0
13 4
14 3
15 1

About Cagri Ozcaglar

Cagri Ozcaglar is a scholar working on Infectious Diseases, Epidemiology and Signal Processing, having authored 15 papers that have together received 299 indexed citations. Recurring topics across this work include Tuberculosis Research and Epidemiology (9 papers), Mycobacterium research and diagnosis (6 papers) and Machine Learning in Bioinformatics (4 papers). The work is most often cited by research in Modeling and Simulation (48 citations), Infectious Diseases (135 citations) and Computational Mathematics (4 citations). Cagri Ozcaglar has collaborated with scholars based in United States and Guadeloupe. Frequent co-authors include Bülent Yener, Kristin P. Bennett, Scott Vandenberg, Lauren S. Cowan, Nalin Rastogi, Sahin Cem Geyik, Krishnaram Kenthapadi, Gungor Polatkan, Hakan Inan and Rohan Ramanath. Their work appears in journals such as BMC Genomics, Mathematical Biosciences and Infection Genetics and Evolution.

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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2026