Mohamed Alloghani
- Artificial Intelligence top 5%
- Health Information Management top 1%
- Information Systems top 10%
- Computer Networks and Communications top 10%
- Computer Vision and Pattern Recognition top 10%
- Co-authors
- Dhiya Al‐JumeilyAhmed J. AljaafJamila MustafinaAbir HussainThar BakerMohammed M. AlaniMohammed KhalafChristopher Thron
- Topics
- Artificial Intelligence in Healthcare (5 papers)Online Learning and Analytics (3 papers)IoT and Edge/Fog Computing (3 papers)
- Journals
- Journal of Biomedical InformaticsJournal of Medical SystemsBMC Medical Informatics and Decision Making
- Partner nations
- United KingdomRussiaIraq
In The Last Decade
Mohamed Alloghani
29 papers receiving 783 citations
Hit Papers
Peers
Comparison fields: 5 of 155
- Artificial Intelligence 259
- Health Information Management 146
- Information Systems 96
- Computer Networks and Communications 76
- Computer Vision and Pattern Recognition 73
Countries citing papers authored by Mohamed Alloghani
This map shows the geographic impact of Mohamed Alloghani'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 Mohamed Alloghani with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mohamed Alloghani more than expected).
Fields of papers citing papers by Mohamed Alloghani
This network shows the impact of papers produced by Mohamed Alloghani. 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 Mohamed Alloghani. The network helps show where Mohamed Alloghani may publish in the future.
Co-authorship network of co-authors of Mohamed Alloghani
This figure shows the co-authorship network connecting the top 25 collaborators of Mohamed Alloghani. A scholar is included among the top collaborators of Mohamed Alloghani 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 Mohamed Alloghani. Mohamed Alloghani is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 2 | |
| 3 | 9 | |
| 4 | 22 | |
| 5 | 32 | |
| 6 | 8 | |
| 7 | 1 | |
| 8 | A Systematic Review on Supervised and Unsupervised Machine Learning Algorithms for Data Sciencebreakdown → | 406 |
| 9 | 1 | |
| 10 | 4 | |
| 11 | 68 | |
| 12 | 3 | |
| 13 | 4 | |
| 14 | 45 | |
| 15 | 1 | |
| 16 | 2 | |
| 17 | 10 | |
| 18 | 9 | |
| 19 | 2 | |
| 20 | 2 |
About Mohamed Alloghani
Mohamed Alloghani is a scholar working on Health Information Management, Computer Science Applications and Health Informatics, having authored 30 papers that have together received 817 indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare (5 papers), Online Learning and Analytics (3 papers) and IoT and Edge/Fog Computing (3 papers). The work is most often cited by research in Health Information Management (146 citations), Health Informatics (40 citations) and Medical Laboratory Technology (17 citations). Mohamed Alloghani has collaborated with scholars based in United Kingdom, Russia and Iraq. Frequent co-authors include Dhiya Al‐Jumeily, Ahmed J. Aljaaf, Jamila Mustafina, Abir Hussain, Thar Baker, Abir Hussain, Mohammed M. Alani, Mohammed Khalaf, Christopher Thron and Conor Mallucci. Their work appears in journals such as Journal of Biomedical Informatics, Journal of Medical Systems and BMC Medical Informatics and Decision Making.
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.