Muhammad Binsawad

473 total citations
32 papers, 298 citations indexed

About

Muhammad Binsawad is a scholar working on Artificial Intelligence, Information Systems and Computer Networks and Communications. According to data from OpenAlex, Muhammad Binsawad has authored 32 papers receiving a total of 298 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Artificial Intelligence, 8 papers in Information Systems and 6 papers in Computer Networks and Communications. Recurrent topics in Muhammad Binsawad's work include Network Security and Intrusion Detection (4 papers), Artificial Intelligence in Healthcare (4 papers) and Technology Adoption and User Behaviour (4 papers). Muhammad Binsawad is often cited by papers focused on Network Security and Intrusion Detection (4 papers), Artificial Intelligence in Healthcare (4 papers) and Technology Adoption and User Behaviour (4 papers). Muhammad Binsawad collaborates with scholars based in Saudi Arabia, Pakistan and Australia. Muhammad Binsawad's co-authors include Marwan Ali Albahar, Osama Sohaib, Igor Hawryszkiewycz, Rahim Khan, Jehad Ali, Muhammad Adil, Alhuseen Omar Alsayed, Ghazanfar Ali Abbasi, Qui Thanh Hoai Ta and Mohammed Amin Almaiah and has published in prestigious journals such as IEEE Access, Sustainability and Journal of the Association for Information Systems.

In The Last Decade

Muhammad Binsawad

30 papers receiving 283 citations

Peers

Muhammad Binsawad

CNC

SPS

ISM

Khalaf Khatatneh Jordan

Carol Springer Sargent United States

S. Srinivasan United States

Mary Agoyi Cyprus

Dietmar Nedbal Austria

Arry Akhmad Arman Indonesia

Cristian Ciurea Romania

Nipon Charoenkitkarn Thailand

Reza Tadayoni Denmark

Abrar Ullah Pakistan

Khalaf Khatatneh Jordan

Muhammad Binsawad

50 ×0.6

CNC

96 ×1.3

43 ×0.7

33 ×0.7

SPS

32 ×0.8

ISM

Citations per year, relative to Muhammad Binsawad Muhammad Binsawad (= 1×) peers Khalaf Khatatneh

Countries citing papers authored by Muhammad Binsawad

Since Specialization

Citations

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

Fields of papers citing papers by Muhammad Binsawad

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Muhammad Binsawad

This figure shows the co-authorship network connecting the top 25 collaborators of Muhammad Binsawad. A scholar is included among the top collaborators of Muhammad Binsawad 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 Muhammad Binsawad. Muhammad Binsawad 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

Alsayed, Alhuseen Omar, et al.. (2025). Leveraging a hybrid convolutional gated recursive diabetes prediction and severity grading model through a mobile app. PeerJ Computer Science. 11. e2642–e2642. 2 indexed citations

Binsawad, Muhammad & Bilal Khan. (2024). Advanced Detection of Abnormal ECG Patterns Using an Optimized LADTree Model with Enhanced Predictive Feature: Potential Application in CKD. Algorithms. 17(9). 406–406.

Binsawad, Muhammad. (2024). Enhancing kidney disease prediction with optimized forest and ECG signals data. Heliyon. 10(10). e30792–e30792. 1 indexed citations

Binsawad, Muhammad & Bilal Khan. (2024). FEPP: Advancing Software Risk Prediction in Requirements Engineering Through Innovative Rule Extraction and Multi-Class Integration. IEEE Access. 12. 59851–59860. 1 indexed citations

Abbas, Haider, et al.. (2024). Secure semantic search using deep learning in a blockchain-assisted multi-user setting. Journal of Cloud Computing Advances Systems and Applications. 13(1). 1 indexed citations

Albashrawi, Mousa, et al.. (2022). Moving to Digital-Healthy Society: Empathy, Sympathy, and Wellbeing in Social Media. Pacific Asia journal of the Association for Information Systems. 14. 71–89. 4 indexed citations

Binsawad, Muhammad & Marwan Ali Albahar. (2022). A Technology Survey on IoT Applications Serving Umrah and Hajj. Applied Computational Intelligence and Soft Computing. 2022. 1–10. 13 indexed citations

Albahar, Marwan Ali, et al.. (2021). Computational Learning Model for Prediction of Heart Disease Using Machine Learning Based on a New Regularizer. Computational Intelligence and Neuroscience. 2021(1). 8628335–8628335. 9 indexed citations

Khan, Bilal, Rashid Naseem, Muhammad Binsawad, Muzammil Khan, & Arshad Ahmad. (2020). Software Cost Estimation Using Flower Pollination Algorithm. 網際網路技術學刊. 21(5). 1243–1251. 7 indexed citations

10.

Hassan, Asif, et al.. (2020). An Ensemble-Learning Based Application to Predict the Earlier Stages of Alzheimer’s Disease (AD). IEEE Access. 8. 222126–222143. 20 indexed citations

11.

Khan, Rafiullah, Arshad Ahmad, Alhuseen Omar Alsayed, et al.. (2020). QuPiD Attack: Machine Learning-Based Privacy Quantification Mechanism for PIR Protocols in Health-Related Web Search. Scientific Programming. 2020. 1–11. 11 indexed citations

12.

Albahar, Marwan Ali, et al.. (2020). An Empirical Comparison on Malicious Activity Detection Using Different Neural Network-Based Models. IEEE Access. 8. 61549–61564. 4 indexed citations

13.

Adil, Muhammad, Rahim Khan, Mohammed Amin Almaiah, et al.. (2020). An Efficient Load Balancing Scheme of Energy Gauge Nodes to Maximize the Lifespan of Constraint Oriented Networks. IEEE Access. 8. 148510–148527. 41 indexed citations

14.

Albahar, Marwan Ali, et al.. (2020). An Efficient Person Re-Identification Model Based on New Regularization Technique. IEEE Access. 8. 171049–171057. 5 indexed citations

15.

Albahar, Marwan Ali & Muhammad Binsawad. (2020). Deep Autoencoders and Feedforward Networks Based on a New Regularization for Anomaly Detection. Security and Communication Networks. 2020. 1–9. 12 indexed citations

16.

Hawryszkiewycz, Igor, et al.. (2019). Factors Affecting the Saudi Arabian Higher Education Creative Environment. Journal of the Association for Information Systems. 3 indexed citations

17.

Binsawad, Muhammad, et al.. (2018). Individual creativity towards technology business incubator performance. Journal of the Association for Information Systems. 2 indexed citations

18.

Binsawad, Muhammad, Osama Sohaib, & Igor Hawryszkiewycz. (2017). Knowledge-Sharing in Technology Business Incubator.. Journal of the Association for Information Systems. 4 indexed citations

19.

Binsawad, Muhammad, Igor Hawryszkiewycz, & Kyeong Kang. (2016). The Influence of the Knowledge-Sharing Process on Technology Business Incubator Performance in Saudi Arabia. UTS ePRESS (University of Technology Sydney). 1 indexed citations

20.

Hawryszkiewycz, Igor, et al.. (2016). Classifying knowledge-sharing barriers by organisational structure in order to find ways to remove these barriers. 3. 73–78. 3 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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