Belal Alsinglawi

1.0k total citations
30 papers, 607 citations indexed

About

Belal Alsinglawi is a scholar working on Computer Networks and Communications, Radiology, Nuclear Medicine and Imaging and Economics and Econometrics. According to data from OpenAlex, Belal Alsinglawi has authored 30 papers receiving a total of 607 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Computer Networks and Communications, 6 papers in Radiology, Nuclear Medicine and Imaging and 5 papers in Economics and Econometrics. Recurrent topics in Belal Alsinglawi's work include COVID-19 epidemiological studies (5 papers), COVID-19 Pandemic Impacts (5 papers) and COVID-19 diagnosis using AI (5 papers). Belal Alsinglawi is often cited by papers focused on COVID-19 epidemiological studies (5 papers), COVID-19 Pandemic Impacts (5 papers) and COVID-19 diagnosis using AI (5 papers). Belal Alsinglawi collaborates with scholars based in Australia, United Arab Emirates and Jordan. Belal Alsinglawi's co-authors include Omar Mubin, Fady Alnajjar, Mahmoud Elkhodr, Abdullah Al Mahmud, Mohammed Alorjani, Omar Darwish, Mohammad Dahman Alshehri, Tahmina Nasrin Poly, Md. Mohaimenul Islam and Zainab Iftikhar and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and IEEE Access.

In The Last Decade

Belal Alsinglawi

28 papers receiving 591 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Belal Alsinglawi Australia 13 141 99 98 89 62 30 607
Marjan Ghazisaeedi Iran 18 105 0.7× 64 0.6× 53 0.5× 68 0.8× 92 1.5× 85 1.0k
Andreas Triantafyllidis Greece 18 113 0.8× 106 1.1× 28 0.3× 55 0.6× 55 0.9× 48 1.0k
Peyman Rezaei‐Hachesu Iran 12 135 1.0× 50 0.5× 31 0.3× 51 0.6× 79 1.3× 55 740
Taha Samad‐Soltani Iran 13 86 0.6× 47 0.5× 33 0.3× 44 0.5× 49 0.8× 56 675
Tomohiro Kuroda Japan 16 113 0.8× 30 0.3× 34 0.3× 216 2.4× 71 1.1× 165 1.2k
Khadijeh Moulaei Iran 14 93 0.7× 25 0.3× 56 0.6× 112 1.3× 46 0.7× 68 615
Niloofar Mohammadzadeh Iran 15 75 0.5× 41 0.4× 20 0.2× 75 0.8× 44 0.7× 58 789
Z.T. Al-Qaysi Iraq 14 193 1.4× 79 0.8× 12 0.1× 163 1.8× 22 0.4× 34 1.0k
Jwan K. Alwan Iraq 9 223 1.6× 107 1.1× 9 0.1× 162 1.8× 25 0.4× 12 912
Santiago Martínez Norway 13 67 0.5× 46 0.5× 7 0.1× 49 0.6× 43 0.7× 56 706

Countries citing papers authored by Belal Alsinglawi

Since Specialization
Citations

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

Fields of papers citing papers by Belal Alsinglawi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Belal Alsinglawi

This figure shows the co-authorship network connecting the top 25 collaborators of Belal Alsinglawi. A scholar is included among the top collaborators of Belal Alsinglawi 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 Belal Alsinglawi. Belal Alsinglawi 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.
Alhashmi, Saadat M., et al.. (2025). Connecting the Dots: IoT, sustainability, and SDGs. Sustainable Futures. 10. 101170–101170. 1 indexed citations
2.
Alsinglawi, Belal, et al.. (2024). Predicting Hospital Stay Length Using Explainable Machine Learning. IEEE Access. 12. 90571–90585. 6 indexed citations
3.
Alsmadi, Izzat, et al.. (2024). Ensemble-based Cyber Intrusion Detection for Robust Smart City Protection. 124–129. 2 indexed citations
4.
Alsinglawi, Belal, et al.. (2023). Indoor Positioning Using Wi-Fi and Machine Learning for Industry 5.0. 359–362. 4 indexed citations
5.
Alamoodi, A. H., O. S. Albahri, B. B. Zaidan, et al.. (2023). Landscape of sign language research based on smartphone apps: coherent literature analysis, motivations, open challenges, recommendations and future directions for app assessment. Universal Access in the Information Society. 23(2). 687–702. 8 indexed citations
6.
Alsadoon, Abeer, Ghazi Al‐Naymat, Ahmed Hamza Osman, et al.. (2023). DFCV: a framework for evaluation deep learning in early detection and classification of lung cancer. Multimedia Tools and Applications. 82(28). 44387–44430. 8 indexed citations
7.
Alsinglawi, Belal, et al.. (2022). An explainable machine learning framework for lung cancer hospital length of stay prediction. Scientific Reports. 12(1). 607–607. 87 indexed citations
8.
Alorjani, Mohammed, et al.. (2022). Soft Tissue Sarcomas: A 16-Year Experience of a Tertiary Referral Hospital in North Jordan. Medicina. 58(2). 198–198. 2 indexed citations
9.
Tashtoush, Yahya, et al.. (2022). A Classifier to Detect Profit and Non Profit Websites Upon Textual Metrics for Security Purposes. SHILAP Revista de lepidopterología. 16(1). 81–91.
10.
Elkhodr, Mahmoud, Omar Mubin, Zainab Iftikhar, et al.. (2021). Technology, Privacy, and User Opinions of COVID-19 Mobile Apps for Contact Tracing: Systematic Search and Content Analysis. Journal of Medical Internet Research. 23(2). e23467–e23467. 47 indexed citations
11.
Islam, Md. Mohaimenul, Tahmina Nasrin Poly, Belal Alsinglawi, et al.. (2021). Application of Artificial Intelligence in COVID-19 Pandemic: Bibliometric Analysis. Healthcare. 9(4). 441–441. 44 indexed citations
12.
Islam, Md. Mohaimenul, et al.. (2021). A State-of-the-Art Survey on Artificial Intelligence to Fight COVID-19. Journal of Clinical Medicine. 10(9). 1961–1961. 13 indexed citations
13.
Alsinglawi, Belal, Omar Mubin, Fady Alnajjar, et al.. (2021). A simulated measurement for COVID-19 pandemic using the effective reproductive number on an empirical portion of population: epidemiological models. Neural Computing and Applications. 35(31). 22813–22821. 1 indexed citations
14.
Tashtoush, Yahya, et al.. (2021). Enhancing Robots Navigation in Internet of Things Indoor Systems. Computers. 10(11). 153–153. 2 indexed citations
15.
Mubin, Omar, et al.. (2020). Exploring serious games for stroke rehabilitation: a scoping review. Disability and Rehabilitation Assistive Technology. 17(2). 159–165. 51 indexed citations
16.
Arsalan, Mudassar Hassan, Omar Mubin, Fady Alnajjar, Belal Alsinglawi, & Nazar Zaki. (2020). Global and Temporal COVID-19 Risk Evaluation. Frontiers in Public Health. 8. 440–440. 12 indexed citations
17.
Alsinglawi, Belal, Omar Mubin, & Mahmoud Elkhodr. (2020). COVID-19 death toll estimated to reach 3,900 by next Friday, according to AI modelling. 2 indexed citations
18.
Mubin, Omar, et al.. (2019). Exoskeletons With Virtual Reality, Augmented Reality, and Gamification for Stroke Patients’ Rehabilitation: Systematic Review. JMIR Rehabilitation and Assistive Technologies. 6(2). e12010–e12010. 86 indexed citations
19.
Elkhodr, Mahmoud & Belal Alsinglawi. (2019). Data provenance and trust establishment in the Internet of Things. Security and Privacy. 3(3). 18 indexed citations
20.
Elkhodr, Mahmoud, Belal Alsinglawi, & Mohammad Dahman Alshehri. (2018). Data Provenance in the Internet of Things. Victoria University Research Repository (Victoria University). 727–731. 43 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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