Hisham Al-Mubaid

48 papers receiving 483 citations

Peers

Hisham Al-Mubaid
Comparison fields: 5 of 85
  • Artificial Intelligence 299
  • Molecular Biology 260
  • Information Systems 93
  • Computer Vision and Pattern Recognition 36
  • Computational Theory and Mathematics 31
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Countries citing papers authored by Hisham Al-Mubaid

Since Specialization
Citations

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

Fields of papers citing papers by Hisham Al-Mubaid

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hisham Al-Mubaid. 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 Hisham Al-Mubaid. The network helps show where Hisham Al-Mubaid may publish in the future.

Co-authorship network of co-authors of Hisham Al-Mubaid

This figure shows the co-authorship network connecting the top 25 collaborators of Hisham Al-Mubaid. A scholar is included among the top collaborators of Hisham Al-Mubaid 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 Hisham Al-Mubaid. Hisham Al-Mubaid 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
#WorkIndexed citations
1 28
2 3
3
An Investigation Dimension for Understanding and Characterizing Computing Disciplines
0
4 3
5
Assessing Information Systems and Computer Information Systems Programs from a Balanced Scorecard Perspective
1
6
From Expectation to Actual Perception after Experience: A Longitudinal Study of the Perceptions of Student Response Systems
2
7
A Model for Long Term Assessment of Computing and Information Systems Programs
6
8
A Learning Approach for Word Sense Disambiguation in the Biomedical Domain.
1
9
Data Mining and Analysis of Material Data using Feature Clustering for Radiation Shielding.
2
10 7
11
Word Classification: An Experimental Approach with Naïve Bayes.
2
12
Critical Factors Influencing the Service Quality of Information Systems: An Organizational View.
1
13 3
14 10
15 3
16
A Learning-Classification Based Approach for Word Prediction
10
17
A New Gene Selection Technique Using Feature Selection Methodology.
3
18 9
19 79
20 4

About Hisham Al-Mubaid

Hisham Al-Mubaid is a scholar working on Artificial Intelligence, Human Factors and Ergonomics and Molecular Biology, having authored 51 papers that have together received 525 indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (20 papers), Bioinformatics and Genomic Networks (12 papers) and Topic Modeling (11 papers). The work is most often cited by research in Artificial Intelligence (299 citations), Information Systems (93 citations) and Molecular Biology (260 citations). Hisham Al-Mubaid has collaborated with scholars based in United States, Egypt and Saudi Arabia. Frequent co-authors include Ping Chen, Ping Chen, Noushin Ghaffari, Emad Abouel Nasr, Ping Chen, Dan J. Kim, Gary D. Boetticher, Michael Hahsler, Kwok-Bun Yue and Wei Ding. Their work appears in journals such as IEEE Transactions on Knowledge and Data Engineering, Journal of the Association for Information Systems and The Scientific World JOURNAL.

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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