Ebrahim Mohammed Senan

2.0k total citations · 2 hit papers
31 papers, 1.3k citations indexed

About

Ebrahim Mohammed Senan is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Neurology. According to data from OpenAlex, Ebrahim Mohammed Senan has authored 31 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Artificial Intelligence, 12 papers in Radiology, Nuclear Medicine and Imaging and 10 papers in Neurology. Recurrent topics in Ebrahim Mohammed Senan's work include AI in cancer detection (19 papers), Brain Tumor Detection and Classification (10 papers) and Radiomics and Machine Learning in Medical Imaging (6 papers). Ebrahim Mohammed Senan is often cited by papers focused on AI in cancer detection (19 papers), Brain Tumor Detection and Classification (10 papers) and Radiomics and Machine Learning in Medical Imaging (6 papers). Ebrahim Mohammed Senan collaborates with scholars based in Saudi Arabia, India and Yemen. Ebrahim Mohammed Senan's co-authors include Mukti E. Jadhav, Ibrahim Abunadi, Suliman Mohamed Fati, Taha H. Rassem, Badiea Abdulkarem Mohammed, Zeyad Ghaleb Al-Mekhlafi, Theyazn H. H. Aldhyani, Ibrahim Abdulrab Ahmed, Mosleh Hmoud Al-Adhaileh and Fawaz Waselallah Alsaade and has published in prestigious journals such as PLoS ONE, Scientific Reports and Sensors.

In The Last Decade

Ebrahim Mohammed Senan

29 papers receiving 1.2k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Diagnosis of Chronic Kidney Disease Using Effective Classification Algorithms and Recursive Feature Elimination Techniques

2021 163 citations Ebrahim Mohammed Senan, Mosleh Hmoud Al-Adhaileh et al. Journal of Healthcare Engineering profile →
Eye Tracking-Based Diagnosis and Early Detection of Autism Spectrum Disorder Using Machine Learning and Deep Learning Techniques

2022 122 citations Ibrahim Abdulrab Ahmed, Ebrahim Mohammed Senan et al. Electronics profile →

Peers

Ebrahim Mohammed Senan

RNMI

CVPR

NEURO

ONCOL

Mukti E. Jadhav India

Sajid Iqbal Pakistan

Marwa Obayya Saudi Arabia

Zhicheng Jiao United States

Hiam Alquran Jordan

Haoyuan Chen China

Seyed‐Ahmad Ahmadi Germany

Samir S. Yadav India

Ali Mohammad Alqudah Jordan

Mukti E. Jadhav India

Ebrahim Mohammed Senan

256 ×0.4

146 ×0.3

RNMI

132 ×0.4

CVPR

126 ×0.4

NEURO

106 ×0.5

ONCOL

Citations per year, relative to Ebrahim Mohammed Senan Ebrahim Mohammed Senan (= 1×) peers Mukti E. Jadhav

Countries citing papers authored by Ebrahim Mohammed Senan

Since Specialization

Citations

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

Fields of papers citing papers by Ebrahim Mohammed Senan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ebrahim Mohammed Senan. 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 Ebrahim Mohammed Senan. The network helps show where Ebrahim Mohammed Senan may publish in the future.

Co-authorship network of co-authors of Ebrahim Mohammed Senan

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Senan, Ebrahim Mohammed, et al.. (2025). Feature Engineering Methods for Analyzing Blood Samples for Early Diagnosis of Hepatitis Using Machine Learning Approaches. Computer Modeling in Engineering & Sciences. 142(3). 3229–3254.

Asiri, Yousef, et al.. (2025). Analyzing histopathological images using fused CNN features based on the geometric active contour method for early diagnosis of lung and colon cancer. Discover Oncology. 16(1). 2036–2036.

Senan, Ebrahim Mohammed, et al.. (2025). Enhanced early skin cancer detection through fusion of vision transformer and CNN features using hybrid attention of EViT-Dens169. Scientific Reports. 15(1). 34776–34776. 1 indexed citations

Khadidos, Alaa O., et al.. (2025). Early detection of Alzheimer’s disease progression stages using hybrid of CNN and transformer encoder models. Scientific Reports. 15(1). 16799–16799. 2 indexed citations

Alayba, Abdulaziz M., Ebrahim Mohammed Senan, & Jalawi Sulaiman Alshudukhi. (2024). Enhancing early detection of Alzheimer’s disease through hybrid models based on feature fusion of multi-CNN and handcrafted features. Scientific Reports. 14(1). 31203–31203. 7 indexed citations

Senan, Ebrahim Mohammed, et al.. (2024). Analysis of dermoscopy images of multi-class for early detection of skin lesions by hybrid systems based on integrating features of CNN models. PLoS ONE. 19(3). e0298305–e0298305. 5 indexed citations

Ahmed, Khalid, et al.. (2023). Automatic Analysis of MRI Images for Early Prediction of Alzheimer’s Disease Stages Based on Hybrid Features of CNN and Handcrafted Features. Diagnostics. 13(9). 1654–1654. 25 indexed citations

Ahmed, Ibrahim Abdulrab, Ebrahim Mohammed Senan, & Hamzeh Salameh Ahmad Shatnawi. (2023). Analysis of Histopathological Images for Early Diagnosis of Oral Squamous Cell Carcinoma by Hybrid Systems Based on CNN Fusion Features. International Journal of Intelligent Systems. 2023(1). 14 indexed citations

Senan, Ebrahim Mohammed, et al.. (2023). Multi-Method Diagnosis of Histopathological Images for Early Detection of Breast Cancer Based on Hybrid and Deep Learning. Mathematics. 11(6). 1429–1429. 21 indexed citations

10.

Senan, Ebrahim Mohammed, et al.. (2023). Predicting of diabetic retinopathy development stages of fundus images using deep learning based on combined features. PLoS ONE. 18(10). e0289555–e0289555. 11 indexed citations

11.

Ahmed, Ibrahim Abdulrab, et al.. (2023). Hybrid Techniques for the Diagnosis of Acute Lymphoblastic Leukemia Based on Fusion of CNN Features. Diagnostics. 13(6). 1026–1026. 26 indexed citations

12.

Fati, Suliman Mohamed, Ebrahim Mohammed Senan, & Yasir Javed. (2022). Early Diagnosis of Oral Squamous Cell Carcinoma Based on Histopathological Images Using Deep and Hybrid Learning Approaches. Diagnostics. 12(8). 1899–1899. 42 indexed citations

13.

Senan, Ebrahim Mohammed, Mukti E. Jadhav, Taha H. Rassem, et al.. (2022). Early Diagnosis of Brain Tumour MRI Images Using Hybrid Techniques between Deep and Machine Learning. Computational and Mathematical Methods in Medicine. 2022. 1–17. 118 indexed citations

14.

Abunadi, Ibrahim & Ebrahim Mohammed Senan. (2022). Multi-Method Diagnosis of Blood Microscopic Sample for Early Detection of Acute Lymphoblastic Leukemia Based on Deep Learning and Hybrid Techniques. Sensors. 22(4). 1629–1629. 58 indexed citations

15.

Al-Mekhlafi, Zeyad Ghaleb, Ebrahim Mohammed Senan, Badiea Abdulkarem Mohammed, et al.. (2022). Diagnosis of Histopathological Images to Distinguish Types of Malignant Lymphomas Using Hybrid Techniques Based on Fusion Features. Electronics. 11(18). 2865–2865. 16 indexed citations

16.

Al-Mekhlafi, Zeyad Ghaleb, Ebrahim Mohammed Senan, Taha H. Rassem, et al.. (2022). Deep Learning and Machine Learning for Early Detection of Stroke and Haemorrhage. Computers, materials & continua/Computers, materials & continua (Print). 72(1). 775–796. 40 indexed citations

17.

Fati, Suliman Mohamed, et al.. (2022). Deep and Hybrid Learning Technique for Early Detection of Tuberculosis Based on X-ray Images Using Feature Fusion. Applied Sciences. 12(14). 7092–7092. 46 indexed citations

18.

Senan, Ebrahim Mohammed, Ali Alzahrani, Mohammed Alzahrani, Nizar Alsharif, & Theyazn H. H. Aldhyani. (2021). Automated Diagnosis of Chest X-Ray for Early Detection of COVID-19 Disease. Computational and Mathematical Methods in Medicine. 2021. 1–10. 19 indexed citations

19.

Senan, Ebrahim Mohammed, et al.. (2021). Classification of Histopathological Images for Early Detection of Breast Cancer Using Deep Learning. Journal of Applied Science and Engineering. 24(3). 323–329. 53 indexed citations

20.

Senan, Ebrahim Mohammed, Mosleh Hmoud Al-Adhaileh, Fawaz Waselallah Alsaade, et al.. (2021). Diagnosis of Chronic Kidney Disease Using Effective Classification Algorithms and Recursive Feature Elimination Techniques. Journal of Healthcare Engineering. 2021. 1–10. 163 indexed citations breakdown →

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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