Oğuz Ata

445 total citations
36 papers, 263 citations indexed

About

Oğuz Ata is a scholar working on Artificial Intelligence, Computer Networks and Communications and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Oğuz Ata has authored 36 papers receiving a total of 263 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 8 papers in Computer Networks and Communications and 6 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Oğuz Ata's work include Artificial Intelligence in Healthcare (5 papers), Imbalanced Data Classification Techniques (5 papers) and SARS-CoV-2 and COVID-19 Research (4 papers). Oğuz Ata is often cited by papers focused on Artificial Intelligence in Healthcare (5 papers), Imbalanced Data Classification Techniques (5 papers) and SARS-CoV-2 and COVID-19 Research (4 papers). Oğuz Ata collaborates with scholars based in Türkiye, Iraq and Saudi Arabia. Oğuz Ata's co-authors include Dilek Turgut‐Balik, Özal Mutlu, Mohammad Azam Ansari, Mohammad N. Alomary, Mazen Almehmadi, Saad Alghamdi, Omar Hussein Salman, Abdullahi Abdu İbrahim, Tareq Abed Mohammed and Aydoḡan Özdemir and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Access and International Journal of Biological Macromolecules.

In The Last Decade

Oğuz Ata

34 papers receiving 255 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Oğuz Ata Türkiye 10 81 63 38 36 36 36 263
Suha Mohammed Hadi Iraq 6 33 0.4× 118 1.9× 30 0.8× 17 0.5× 28 0.8× 19 313
Julian Matschinske Germany 7 39 0.5× 109 1.7× 7 0.2× 60 1.7× 19 0.5× 11 247
M.A. Abo-Elsoud Egypt 6 30 0.4× 169 2.7× 19 0.5× 15 0.4× 27 0.8× 19 331
Sani Sharif Usman Nigeria 7 52 0.6× 206 3.3× 22 0.6× 36 1.0× 32 0.9× 8 450
Khalid Shaker Iraq 9 18 0.2× 118 1.9× 20 0.5× 12 0.3× 27 0.8× 28 240
R. Rathipriya India 8 18 0.2× 120 1.9× 11 0.3× 17 0.5× 24 0.7× 39 270
Mubarak Taiwo Mustapha Cyprus 11 27 0.3× 134 2.1× 4 0.1× 27 0.8× 20 0.6× 22 412
Marco Postiglione Italy 10 9 0.1× 112 1.8× 25 0.7× 25 0.7× 23 0.6× 31 279
Nusrat Rouf India 3 19 0.2× 135 2.1× 13 0.3× 11 0.3× 28 0.8× 5 342
M. Todd Young United States 8 13 0.2× 197 3.1× 7 0.2× 110 3.1× 14 0.4× 13 335

Countries citing papers authored by Oğuz Ata

Since Specialization
Citations

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

Fields of papers citing papers by Oğuz Ata

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Oğuz Ata

This figure shows the co-authorship network connecting the top 25 collaborators of Oğuz Ata. A scholar is included among the top collaborators of Oğuz Ata 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 Oğuz Ata. Oğuz Ata 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
1.
Ata, Oğuz, et al.. (2026). HQML-NLP: A hybrid quantum machine learning framework for scholarly AI-text detection. Applied Soft Computing. 191. 114634–114634.
2.
Ata, Oğuz, et al.. (2025). Bridging the Gap: Ensemble Learning-Based NLP Framework for AI-Generated Text Identification in Academia. The International Arab Journal of Information Technology. 22(6). 1 indexed citations
3.
Ata, Oğuz, et al.. (2025). HawkFish Optimization Algorithm: A Gender-Bending Approach for Solving Complex Optimization Problems. Electronics. 14(3). 611–611. 6 indexed citations
4.
Ata, Oğuz, et al.. (2024). e-Diagnostic system for diabetes disease prediction on an IoMT environment-based hyper AdaBoost machine learning model. The Journal of Supercomputing. 80(11). 15664–15689. 4 indexed citations
5.
Ata, Oğuz, et al.. (2024). Obstacle Avoidance Capability for Multi-Target Path Planning in Different Styles of Search. Computers, materials & continua/Computers, materials & continua (Print). 81(1). 749–771.
6.
Ata, Oğuz, et al.. (2024). Multisource Data Framework for Prehospital Emergency Triage in Real-Time IoMT-Based Telemedicine Systems. International Journal of Medical Informatics. 192. 105608–105608. 3 indexed citations
7.
Ata, Oğuz, et al.. (2024). ENHANCING IIOT SECURITY WITH MACHINE LEARNING AND DEEP LEARNING FOR INTRUSION DETECTION. Malaysian Journal of Computer Science. 37(2). 139–153. 1 indexed citations
8.
Ata, Oğuz, et al.. (2024). A comprehensive analysis and performance evaluation for osteoporosis prediction models. PeerJ Computer Science. 10. e2338–e2338. 1 indexed citations
9.
Ata, Oğuz, et al.. (2023). Enhancing Self-Care Prediction in Children with Impairments: A Novel Framework for Addressing Imbalance and High Dimensionality. Applied Sciences. 14(1). 356–356. 1 indexed citations
10.
Ata, Oğuz, et al.. (2023). Classification of melanonychia, Beau’s lines, and nail clubbing based on nail images and transfer learning techniques. PeerJ Computer Science. 9. e1533–e1533. 9 indexed citations
11.
Ata, Oğuz, et al.. (2022). Diagnosing Coronary Artery Disease on the Basis of Hard Ensemble Voting Optimization. Medicina. 58(12). 1745–1745. 8 indexed citations
12.
Ata, Oğuz, et al.. (2022). Diagnosing Cervical Cancer Using Machine Learning Methods. 6. 1–3. 10 indexed citations
13.
Ata, Oğuz, et al.. (2022). Multi-objective deep learning framework for COVID-19 dataset problems. Journal of King Saud University - Science. 35(3). 102527–102527. 8 indexed citations
14.
Ata, Oğuz, et al.. (2022). Novel hybrid classification model for multi-class imbalanced lithology dataset. Optik. 270. 170047–170047. 2 indexed citations
15.
Ata, Oğuz, et al.. (2020). Comparative Analysis of Different Distributions Dataset by Using Data Mining Techniques on Credit Card Fraud Detection. SHILAP Revista de lepidopterología. 1 indexed citations
16.
Mutlu, Özal, et al.. (2020). Targeting SARS-CoV-2 Nsp12/Nsp8 interaction interface with approved and investigational drugs: an in silico structure-based approach. Journal of Biomolecular Structure and Dynamics. 40(2). 918–930. 22 indexed citations
17.
Mutlu, Özal, et al.. (2020). Evaluation of the potency of FDA-approved drugs on wild type and mutant SARS-CoV-2 helicase (Nsp13). International Journal of Biological Macromolecules. 163. 1687–1696. 28 indexed citations
18.
Ata, Oğuz, et al.. (2020). An updated analysis of variations in SARS-CoV-2 genome. TURKISH JOURNAL OF BIOLOGY. 44(3). 157–167. 44 indexed citations
19.
Ata, Oğuz, et al.. (2020). Comparative Analysis of Different Distributions Dataset by Using Data Mining Techniques on Credit Card Fraud Detection. Tehnicki vjesnik - Technical Gazette. 27(2). 11 indexed citations
20.
Ata, Oğuz, Hasan H. Balık, & Erdem Uçar. (2017). Protocol Design for Secure Communication in WSN. TEM Journal. 192–204. 1 indexed citations

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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