Suat Toraman

834 total citations
33 papers, 601 citations indexed

About

Suat Toraman is a scholar working on Molecular Biology, Cognitive Neuroscience and Automotive Engineering. According to data from OpenAlex, Suat Toraman has authored 33 papers receiving a total of 601 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 7 papers in Cognitive Neuroscience and 6 papers in Automotive Engineering. Recurrent topics in Suat Toraman's work include EEG and Brain-Computer Interfaces (7 papers), Spectroscopy Techniques in Biomedical and Chemical Research (6 papers) and Machine Learning in Bioinformatics (5 papers). Suat Toraman is often cited by papers focused on EEG and Brain-Computer Interfaces (7 papers), Spectroscopy Techniques in Biomedical and Chemical Research (6 papers) and Machine Learning in Bioinformatics (5 papers). Suat Toraman collaborates with scholars based in Türkiye and Poland. Suat Toraman's co-authors include İbrahim Türkoğlu, Talha Burak Alakuş, Seda Arslan Tuncer, Bihter Daş, Hakan Aygün, Zozan Güleken, Rabia Bilici, Serap Erdem Kuruca, Oğuzhan Gündüz and Bilal Üstündağ and has published in prestigious journals such as Energy, Environmental Science and Pollution Research and Chaos Solitons & Fractals.

In The Last Decade

Suat Toraman

30 papers receiving 578 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Suat Toraman Türkiye 12 227 198 74 71 62 33 601
Nathan Gaw United States 8 176 0.8× 131 0.7× 95 1.3× 36 0.5× 21 0.3× 20 534
Vassili Kovalev Belarus 15 264 1.2× 186 0.9× 108 1.5× 339 4.8× 89 1.4× 59 830
Gongbo Liang United States 13 180 0.8× 232 1.2× 26 0.4× 81 1.1× 9 0.1× 38 479
Haijun Lei China 16 192 0.8× 201 1.0× 40 0.5× 434 6.1× 32 0.5× 58 865
Seda Arslan Tuncer Türkiye 13 113 0.5× 148 0.7× 118 1.6× 165 2.3× 12 0.2× 55 542
Tommy Löfstedt Sweden 14 187 0.8× 144 0.7× 48 0.6× 103 1.5× 18 0.3× 35 754
Sang‐Woong Lee South Korea 10 116 0.5× 232 1.2× 69 0.9× 212 3.0× 16 0.3× 19 519
C. Jiménez-Mesa Spain 9 120 0.5× 138 0.7× 93 1.3× 101 1.4× 11 0.2× 14 449
Muhammad Yaqub China 16 142 0.6× 222 1.1× 40 0.5× 165 2.3× 18 0.3× 46 856

Countries citing papers authored by Suat Toraman

Since Specialization
Citations

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

Fields of papers citing papers by Suat Toraman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Suat Toraman

This figure shows the co-authorship network connecting the top 25 collaborators of Suat Toraman. A scholar is included among the top collaborators of Suat Toraman 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 Suat Toraman. Suat Toraman 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.
Toraman, Suat, et al.. (2025). Prediction of noise of commercial aircraft based on itself specifications by using machine learning methods. Journal of Air Transport Management. 125. 102779–102779. 2 indexed citations
2.
3.
Toraman, Suat, et al.. (2024). Machine learning application to forecasting performance and thermodynamics parameters of small turbojet engine. Journal of Thermal Analysis and Calorimetry. 150(1). 505–519. 1 indexed citations
4.
Aygün, Hakan, et al.. (2024). Prediction of performance characteristics of an experimental micro turbojet engine using machine learning approaches. Energy. 313. 133997–133997. 5 indexed citations
5.
6.
Aygün, Hakan, et al.. (2023). Machine learning based approach for forecasting emission parameters of mixed flow turbofan engine at high power modes. Energy. 271. 127026–127026. 23 indexed citations
7.
Daş, Bihter & Suat Toraman. (2023). New Coronavirus 2 (SARS-CoV-2) Detection Method from Human Nucleic Acid Sequences Using Capsule Networks. Brazilian Archives of Biology and Technology. 66. 3 indexed citations
8.
Toraman, Suat, et al.. (2022). Deep learning approach for prediction of exergy and emission parameters of commercial high by-pass turbofan engines. Environmental Science and Pollution Research. 30(10). 27539–27559. 10 indexed citations
9.
Toraman, Suat, et al.. (2022). Modeling of performance and thermodynamic metrics of a conceptual turboprop engine by comparing different machine learning approaches. International Journal of Energy Research. 46(15). 21084–21103. 8 indexed citations
10.
Onat, Cem, et al.. (2021). Prediction of combustion states from flame image in a domestic coal burner. Measurement Science and Technology. 32(7). 75403–75403. 7 indexed citations
11.
Toraman, Suat, et al.. (2021). Uzun Kısa Vadeli Bellek Yöntemi ile Havayolu Yolcu Tahmini. Journal of Aviation. 5(2). 241–248. 4 indexed citations
12.
Toraman, Suat, Talha Burak Alakuş, & İbrahim Türkoğlu. (2020). Convolutional capsnet: A novel artificial neural network approach to detect COVID-19 disease from X-ray images using capsule networks. Chaos Solitons & Fractals. 140. 110122–110122. 232 indexed citations
13.
Toraman, Suat. (2020). Preictal and Interictal Recognition for Epileptic Seizure Prediction Using Pre-trained 2D-CNN Models. Traitement du signal. 37(6). 1045–1054. 22 indexed citations
14.
Daş, Bihter & Suat Toraman. (2020). Classifying Protein Sequences Using Convolutional Neural Network. Bitlis Eren Üniversitesi Fen Bilimleri Dergisi. 9(4). 1663–1671. 3 indexed citations
15.
Güleken, Zozan, et al.. (2020). Investigation of the discrimination and characterization of blood serum structure in patients with opioid use disorder using IR spectroscopy and PCA-LDA analysis. Journal of Pharmaceutical and Biomedical Analysis. 190. 113553–113553. 41 indexed citations
16.
Toraman, Suat, et al.. (2019). Is it possible to detect cerebral dominance via EEG signals by using deep learning?. Medical Hypotheses. 131. 109315–109315. 21 indexed citations
17.
Tuncer, Seda Arslan, et al.. (2019). A deep learning-based decision support system for diagnosis of OSAS using PTT signals. Medical Hypotheses. 127. 15–22. 49 indexed citations
18.
Toraman, Suat & İbrahim Türkoğlu. (2018). Derin Öğrenme ile FTIR Sinyallerinden Kolon Kanseri Riskinin Belirlenmesi. DergiPark (Istanbul University). 30(3). 115–120. 1 indexed citations
19.
Toraman, Suat, et al.. (2017). COMPARISON OF THE CLASSIFICATION PERFORMANCES OF CRIMINAL TENDENCIES OF SCHIZOPHRENIC PATIENTS BY ARTIFICIAL NEURAL NETWORKS AND SUPPORT VECTOR MACHINE. DergiPark (Istanbul University). 7(2). 177–185. 2 indexed citations
20.
Türkoğlu, İbrahim & Suat Toraman. (2013). KARAR AĞAÇLARI VE FRAKTAL ANALİZ KULLANARAK HİSTOPATOLOJİK İMGELERİN SINIFLANDIRILMASI. 22(4). 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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