Rahime Ceylan

833 total citations
24 papers, 618 citations indexed

About

Rahime Ceylan is a scholar working on Radiology, Nuclear Medicine and Imaging, Cardiology and Cardiovascular Medicine and Artificial Intelligence. According to data from OpenAlex, Rahime Ceylan has authored 24 papers receiving a total of 618 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Radiology, Nuclear Medicine and Imaging, 9 papers in Cardiology and Cardiovascular Medicine and 8 papers in Artificial Intelligence. Recurrent topics in Rahime Ceylan's work include ECG Monitoring and Analysis (8 papers), Radiomics and Machine Learning in Medical Imaging (7 papers) and EEG and Brain-Computer Interfaces (6 papers). Rahime Ceylan is often cited by papers focused on ECG Monitoring and Analysis (8 papers), Radiomics and Machine Learning in Medical Imaging (7 papers) and EEG and Brain-Computer Interfaces (6 papers). Rahime Ceylan collaborates with scholars based in Türkiye and Pakistan. Rahime Ceylan's co-authors include Yüksel Özbay, Bekir Karlık, Murat Ceylan, Sadık Kara, Musa Hakan Arslan, Fatma Lati̇foğlu, Seral Özşen, Mücahid Barstuğan, Hasan Erdoğan and Mustafa Koplay and has published in prestigious journals such as Expert Systems with Applications, Computer Methods and Programs in Biomedicine and Computers in Biology and Medicine.

In The Last Decade

Rahime Ceylan

21 papers receiving 573 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Rahime Ceylan Türkiye	9	388	299	142	124	86	24	618
Indu Saini India	13	303 0.8×	200 0.7×	196 1.4×	94 0.8×	69 0.8×	70	687
Saroj Kumar Pandey India	14	361 0.9×	294 1.0×	136 1.0×	147 1.2×	40 0.5×	73	737
Ashok Ghatol India	16	247 0.6×	145 0.5×	103 0.7×	331 2.7×	94 1.1×	73	884
Junyuan Shang China	10	431 1.1×	276 0.9×	110 0.8×	267 2.2×	41 0.5×	30	779
Kandala N. V. P. S. Rajesh India	12	265 0.7×	206 0.7×	118 0.8×	85 0.7×	46 0.5×	26	578
Sandeep Raj India	12	500 1.3×	385 1.3×	239 1.7×	44 0.4×	44 0.5×	19	652
Mehmet Korürek Türkiye	11	317 0.8×	252 0.8×	113 0.8×	100 0.8×	85 1.0×	31	520
Arash Gharehbaghi Sweden	13	422 1.1×	207 0.7×	111 0.8×	97 0.8×	129 1.5×	27	738
Ambalika Sharma India	13	211 0.5×	106 0.4×	141 1.0×	65 0.5×	52 0.6×	36	427

Countries citing papers authored by Rahime Ceylan

Since Specialization

Citations

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

Fields of papers citing papers by Rahime Ceylan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rahime Ceylan

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

All Works

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20 of 20 papers shown

Ceylan, Rahime, et al.. (2024). A Novel Deep Learning Model for Pancreas Segmentation: Pascal U-Net. INTELIGENCIA ARTIFICIAL. 27(74). 22–36.

Ceylan, Rahime, et al.. (2023). Adrenal lesion classification with abdomen caps and the effect of ROI size. Physical and Engineering Sciences in Medicine. 46(2). 865–875. 2 indexed citations

Ceylan, Rahime, et al.. (2023). Adrenal Tumor Segmentation on U-Net: A Study About Effect of Different Parameters in Deep Learning. Vietnam Journal of Computer Science. 11(1). 111–135. 1 indexed citations

Ceylan, Rahime, et al.. (2022). Pneumonia Detection with Chest-Caps. Traitement du signal. 39(6). 2211–2216. 1 indexed citations

Ceylan, Rahime, et al.. (2020). Classification of Mammography Images by Transfer Learning. 1–4. 1 indexed citations

Barstuğan, Mücahid, et al.. (2019). Adrenal Tumor Classification on T1 and T2-weighted Abdominal MR Images. 2. 1–7.

Channa, Asma, et al.. (2019). Design and Application of a Smart Diagnostic System for Parkinson’s Patients using Machine Learning. International Journal of Advanced Computer Science and Applications. 10(6). 1 indexed citations

Barstuğan, Mücahid, et al.. (2018). Adrenal tumor segmentation method for MR images. Computer Methods and Programs in Biomedicine. 164. 87–100. 8 indexed citations

Ceylan, Rahime, et al.. (2018). A novel pipeline for adrenal tumour segmentation. Computer Methods and Programs in Biomedicine. 159. 77–86. 12 indexed citations

10.

Ceylan, Rahime, et al.. (2017). Elimination of white Gaussian noise in arterial phase CT images to bring adrenal tumours into the forefront. Computerized Medical Imaging and Graphics. 65. 46–57. 14 indexed citations

11.

Ceylan, Rahime, et al.. (2017). Classification of adrenal lesions by bounded PSO-NN. 1–4. 6 indexed citations

12.

Barstuğan, Mücahid & Rahime Ceylan. (2017). A discriminative dictionary learning-AdaBoost-SVM classification method on imbalanced datasets. 2 indexed citations

13.

Ceylan, Rahime. (2015). Compensatory neurofuzzy model for discrete data classification in biomedical. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 9443. 94432I–94432I. 1 indexed citations

14.

Özşen, Seral & Rahime Ceylan. (2014). Comparison of AIS and fuzzy c-means clustering methods on the classification of breast cancer and diabetes datasets. TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES. 22. 1241–1254. 8 indexed citations

15.

Ceylan, Rahime, Yüksel Özbay, & Bekir Karlık. (2009). Classification of ECG arrhythmias using Type-2 Fuzzy Clustering Neural Network. 45. 1–4. 8 indexed citations

16.

Ceylan, Rahime, Yüksel Özbay, & Bekir Karlık. (2008). A novel approach for classification of ECG arrhythmias: Type-2 fuzzy clustering neural network. Expert Systems with Applications. 36(3). 6721–6726. 134 indexed citations

17.

Özbay, Yüksel, Sadık Kara, Fatma Lati̇foğlu, Rahime Ceylan, & Murat Ceylan. (2007). Complex-valued wavelet artificial neural network for Doppler signals classifying. Artificial Intelligence in Medicine. 40(2). 143–156. 18 indexed citations

18.

Ceylan, Rahime & Yüksel Özbay. (2006). Comparison of FCM, PCA and WT techniques for classification ECG arrhythmias using artificial neural network. Expert Systems with Applications. 33(2). 286–295. 157 indexed citations

19.

Ceylan, Murat, et al.. (2005). Classification of carotid artery Doppler signals in the early phase of atherosclerosis using complex-valued artificial neural network. Computers in Biology and Medicine. 37(1). 28–36. 30 indexed citations

20.

Özbay, Yüksel, Rahime Ceylan, & Bekir Karlık. (2005). A fuzzy clustering neural network architecture for classification of ECG arrhythmias. Computers in Biology and Medicine. 36(4). 376–388. 182 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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