Ibrahim Abunadi

1.5k total citations
46 papers, 911 citations indexed

About

Ibrahim Abunadi is a scholar working on Artificial Intelligence, Information Systems and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Ibrahim Abunadi has authored 46 papers receiving a total of 911 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Artificial Intelligence, 12 papers in Information Systems and 9 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Ibrahim Abunadi's work include AI in cancer detection (9 papers), COVID-19 diagnosis using AI (7 papers) and IoT and Edge/Fog Computing (5 papers). Ibrahim Abunadi is often cited by papers focused on AI in cancer detection (9 papers), COVID-19 diagnosis using AI (7 papers) and IoT and Edge/Fog Computing (5 papers). Ibrahim Abunadi collaborates with scholars based in Saudi Arabia, Pakistan and India. Ibrahim Abunadi's co-authors include Ebrahim Mohammed Senan, Amjad Rehman, Tanzila Saba, Fahd N. Al‐Wesabi, Mamdouh Alenezi, Suliman Mohamed Fati, Souad Larabi-Marie-Sainte, Manar Ahmed Hamza, Sanaa Ghouzali and Mukti E. Jadhav and has published in prestigious journals such as Scientific Reports, IEEE Access and Sensors.

In The Last Decade

Ibrahim Abunadi

44 papers receiving 848 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ibrahim Abunadi Saudi Arabia 18 363 213 157 156 115 46 911
M. Rubaiyat Hossain Mondal Bangladesh 18 518 1.4× 304 1.4× 113 0.7× 123 0.8× 109 0.9× 75 1.2k
Subrato Bharati Bangladesh 17 411 1.1× 290 1.4× 73 0.5× 73 0.5× 99 0.9× 43 887
Zuherman Rustam Indonesia 21 696 1.9× 220 1.0× 206 1.3× 197 1.3× 94 0.8× 147 1.4k
Pundru Chandra Shaker Reddy India 23 421 1.2× 123 0.6× 84 0.5× 113 0.7× 158 1.4× 93 1.1k
Saad Alanazi Saudi Arabia 20 376 1.0× 165 0.8× 132 0.8× 145 0.9× 174 1.5× 84 1.1k
Murat Karabatak Türkiye 13 702 1.9× 304 1.4× 193 1.2× 306 2.0× 62 0.5× 77 1.4k
Junaid Rashid Pakistan 15 347 1.0× 166 0.8× 150 1.0× 194 1.2× 80 0.7× 71 967
Meenu Gupta India 14 465 1.3× 458 2.2× 133 0.8× 222 1.4× 62 0.5× 175 1.2k
Azhar Imran Pakistan 21 447 1.2× 573 2.7× 163 1.0× 310 2.0× 177 1.5× 75 1.3k
Madallah Alruwaili Saudi Arabia 19 326 0.9× 204 1.0× 105 0.7× 179 1.1× 151 1.3× 57 973

Countries citing papers authored by Ibrahim Abunadi

Since Specialization
Citations

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

Fields of papers citing papers by Ibrahim Abunadi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ibrahim Abunadi

This figure shows the co-authorship network connecting the top 25 collaborators of Ibrahim Abunadi. A scholar is included among the top collaborators of Ibrahim Abunadi 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 Ibrahim Abunadi. Ibrahim Abunadi 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.
2.
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
3.
Rehman, Amjad, et al.. (2024). An intelligent deep augmented model for detection of banana leaves diseases. Microscopy Research and Technique. 88(1). 53–64. 2 indexed citations
4.
Ismail, Nor Azman, et al.. (2022). Hybrid CNN Model for Classification of Rumex Obtusifolius in Grassland. IEEE Access. 10. 90940–90957. 17 indexed citations
5.
Alshareef, Abdulrhman M., Raed Alsini, Fadwa Alrowais, et al.. (2022). Optimal Deep Learning Enabled Prostate Cancer Detection Using Microarray Gene Expression. Journal of Healthcare Engineering. 2022. 1–12. 26 indexed citations
6.
Abunadi, Ibrahim, Amani Abdulrahman Albraikan, Jaber S. Alzahrani, et al.. (2022). An Automated Glowworm Swarm Optimization with an Inception-Based Deep Convolutional Neural Network for COVID-19 Diagnosis and Classification. Healthcare. 10(4). 697–697. 24 indexed citations
7.
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
8.
Poonia, Ramesh Chandra, Mukesh Kumar Gupta, Ibrahim Abunadi, et al.. (2022). Intelligent Diagnostic Prediction and Classification Models for Detection of Kidney Disease. Healthcare. 10(2). 371–371. 49 indexed citations
9.
Abunadi, Ibrahim. (2022). Deep and hybrid learning of MRI diagnosis for early detection of the progression stages in Alzheimer’s disease. Connection Science. 34(1). 2395–2430. 26 indexed citations
10.
Abunadi, Ibrahim, Amjad Rehman, Khalid Haseeb, Teg Alam, & Gwanggil Jeon. (2022). A multi‐parametric machine learning approach using authentication trees for the healthcare industry. Expert Systems. 41(2). 7 indexed citations
11.
Abunadi, Ibrahim, Maha M. Althobaiti, Fahd N. Al‐Wesabi, et al.. (2022). Federated Learning with Blockchain Assisted Image Classification for Clustered UAV Networks. Computers, materials & continua/Computers, materials & continua (Print). 72(1). 1195–1212. 35 indexed citations
12.
13.
Saba, Tanzila, et al.. (2021). Machine learning techniques to detect and forecast the daily total COVID‐19 infected and deaths cases under different lockdown types. Microscopy Research and Technique. 84(7). 1462–1474. 38 indexed citations
14.
Abunadi, Ibrahim, et al.. (2021). BSF-EHR: Blockchain Security Framework for Electronic Health Records of Patients. Sensors. 21(8). 2865–2865. 49 indexed citations
15.
Abunadi, Ibrahim, et al.. (2021). Optimizing the transfer‐learning with pretrained deep convolutional neural networks for first stage breast tumor diagnosis using breast ultrasound visual images. Microscopy Research and Technique. 85(4). 1444–1453. 18 indexed citations
16.
Abunadi, Ibrahim & R. Lakshmana Kumar. (2021). Blockchain and Business Process Management in Health Care, Especially for COVID-19 Cases. Security and Communication Networks. 2021. 1–16. 17 indexed citations
17.
Abunadi, Ibrahim & Mamdouh Alenezi. (2020). An Empirical Investigation of Security Vulnerabilities within Web Applications. JUCS - Journal of Universal Computer Science. 22. 537–551. 8 indexed citations
18.
Sameh, Ahmed & Ibrahim Abunadi. (2019). Piecewise multi-regression. 1–7. 1 indexed citations
19.
Abunadi, Ibrahim & Fayez Alqahtani. (2017). Instrument development and contextualization for perceived characteristics of e-transactions. Program electronic library and information systems. 51(1). 52–64. 3 indexed citations
20.
Abunadi, Ibrahim & Mamdouh Alenezi. (2015). Towards Cross Project Vulnerability Prediction in Open Source Web Applications. 1–5. 14 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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