Muhammad Usman

1.3k total citations
59 papers, 863 citations indexed

About

Muhammad Usman is a scholar working on Information Systems, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Muhammad Usman has authored 59 papers receiving a total of 863 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Information Systems, 17 papers in Artificial Intelligence and 11 papers in Computer Vision and Pattern Recognition. Recurrent topics in Muhammad Usman's work include Data Mining Algorithms and Applications (8 papers), Sentiment Analysis and Opinion Mining (7 papers) and Artificial Intelligence in Healthcare (5 papers). Muhammad Usman is often cited by papers focused on Data Mining Algorithms and Applications (8 papers), Sentiment Analysis and Opinion Mining (7 papers) and Artificial Intelligence in Healthcare (5 papers). Muhammad Usman collaborates with scholars based in Pakistan, United States and Macao. Muhammad Usman's co-authors include A.C.M. Fong, Simon Fong, Syed Muhammad Usman, Muhammad Afzaal, Sajid Ali Khan, Ayyaz Hussain, Muhammad Azeem, Azhar Mahmood, Xiao Zhang and Ran Zhang and has published in prestigious journals such as IEEE Communications Magazine, Industrial Marketing Management and Heliyon.

In The Last Decade

Muhammad Usman

54 papers receiving 798 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Muhammad Usman Pakistan	17	244	179	162	144	110	59	863
Priyanka Singh India	18	245 1.0×	81 0.5×	426 2.6×	133 0.9×	111 1.0×	66	809
Rizwan Ahmed Khan Pakistan	14	341 1.4×	92 0.5×	197 1.2×	48 0.3×	86 0.8×	32	807
M. P. S. Bhatia India	19	503 2.1×	45 0.3×	165 1.0×	332 2.3×	170 1.5×	126	1.2k
Guangxu Xun United States	20	872 3.6×	451 2.5×	189 1.2×	528 3.7×	414 3.8×	47	1.7k
Timothy Oladunni United States	10	198 0.8×	96 0.5×	52 0.3×	63 0.4×	45 0.4×	23	559
Eloisa Vargiu Italy	13	161 0.7×	116 0.6×	92 0.6×	124 0.9×	19 0.2×	83	626
Francesco Pinciroli Italy	17	208 0.9×	66 0.4×	49 0.3×	79 0.5×	72 0.7×	114	936
Kevin Leach United States	14	272 1.1×	133 0.7×	36 0.2×	214 1.5×	167 1.5×	52	668
Ramzi A. Haraty Lebanon	16	329 1.3×	17 0.1×	157 1.0×	239 1.7×	97 0.9×	116	989
Seyed Reza Shahamiri New Zealand	16	523 2.1×	102 0.6×	89 0.5×	208 1.4×	321 2.9×	41	957

Countries citing papers authored by Muhammad Usman

Since Specialization

Citations

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

Fields of papers citing papers by Muhammad Usman

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Muhammad Usman

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

Usman, Muhammad, et al.. (2025). B2B digital platform capability and sustainable positioning: Do knowledge depth, knowledge breadth, and agility matter?. Industrial Marketing Management. 130. 46–59.

Ali, Syed Wajahat, et al.. (2025). EDRNet: An attention-based model for multi-type tumor and polyp segmentation in medical imaging. Displays. 88. 103031–103031. 1 indexed citations

Usman, Muhammad, et al.. (2024). Determinants for Sustainable Entrepreneurial Intentions: A Systematic Literature Review. 6(2). 494–512.

Usman, Muhammad, et al.. (2024). Digital Trends and 21st Century Competencies in Educational Transformation. 12(2). 930–939.

Usman, Muhammad, et al.. (2023). Deep learning framework for early detection of COVID-19 using X-ray images. Multimedia Tools and Applications. 83(3). 6883–6908. 7 indexed citations

Usman, Muhammad, et al.. (2023). Development of Science E-modules on Solar System Materials Based on Android for Junior High School Students. 5(1). 58–68. 1 indexed citations

Xia, Wei, Ran Zhang, Xiao Zhang, & Muhammad Usman. (2023). A novel method for diagnosing Alzheimer's disease using deep pyramid CNN based on EEG signals. Heliyon. 9(4). e14858–e14858. 38 indexed citations

Usman, Muhammad, et al.. (2022). Highly accurate phishing URL detection based on machine learning. Journal of Ambient Intelligence and Humanized Computing. 14(7). 9233–9251. 27 indexed citations

Usman, Muhammad, et al.. (2021). Determinants of Students’ Satisfaction in HEIs’ of Pakistan: An Empirical Investigation. Studies of Applied Economics. 39(10). 2 indexed citations

10.

Usman, Muhammad, et al.. (2020). Selecting best predictors from large software repositories for highly accurate software effort estimation. Journal of Software Evolution and Process. 32(10). 6 indexed citations

11.

Afzaal, Muhammad, Muhammad Usman, A.C.M. Fong, & Simon Fong. (2019). Multiaspect‐based opinion classification model for tourist reviews. Expert Systems. 36(2). 21 indexed citations

12.

Afzaal, Muhammad, Muhammad Usman, & A.C.M. Fong. (2019). Tourism Mobile App With Aspect-Based Sentiment Classification Framework for Tourist Reviews. IEEE Transactions on Consumer Electronics. 65(2). 233–242. 62 indexed citations

13.

Usman, Muhammad. (2017). Multi-Level Mining of Association Rules from Warehouse Schema. Kuwait Journal of Science. 44(1). 1 indexed citations

14.

Afzaal, Muhammad, Muhammad Usman, A.C.M. Fong, Simon Fong, & Yan Zhuang. (2016). Fuzzy Aspect Based Opinion Classification System for Mining Tourist Reviews. Advances in Fuzzy Systems. 2016. 1–14. 28 indexed citations

15.

Usman, Muhammad. (2016). Multi-Level Mining and Visualization of Informative Association Rules.. Journal of information science and engineering. 32. 1061–1078. 2 indexed citations

16.

Usman, Muhammad, et al.. (2015). An effective model for aspect based opinion mining for social reviews. 49–56. 9 indexed citations

17.

Khan, Sajid Ali, et al.. (2015). Proficient lungs nodule detection and classification using machine learning techniques. Journal of Intelligent & Fuzzy Systems. 28(2). 905–917. 7 indexed citations

18.

Khan, Sajid Ali, Muhammad Usman, & Naveed Riaz. (2015). Face recognition via optimized features fusion. Journal of Intelligent & Fuzzy Systems. 28(4). 1819–1828. 16 indexed citations

19.

Khan, Sajid Ali, Ayyaz Hussain, Muhammad Usman, et al.. (2014). Robust face recognition using computationally efficient features. Journal of Intelligent & Fuzzy Systems. 27(6). 3131–3143. 10 indexed citations

20.

Cockcroft, Anne, et al.. (2014). Why children are not vaccinated against measles: a cross-sectional study in two Nigerian States. Archives of Public Health. 72(1). 48–48. 26 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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