Monther Alhamdoosh
- Artificial Intelligence top 10%
- Molecular Biology
- Computer Vision and Pattern Recognition top 10%
- Environmental Engineering
- Immunology
- Co-authors
- Dianhui WangMilica NgNicholas J. WilsonMatthew E. RitchieMichael J. WilsonJulie M. SheridanHuy HuynhD. Gabriëls
- Topics
- Machine Learning and ELM (3 papers)Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis (2 papers)Machine Learning in Bioinformatics (2 papers)
- Journals
- CirculationSHILAP Revista de lepidopterologíaBioinformatics
- Partner nations
- AustraliaSwitzerlandUnited Kingdom
In The Last Decade
Monther Alhamdoosh
17 papers receiving 557 citations
Peers
Comparison fields: 5 of 116
- Artificial Intelligence 179
- Molecular Biology 158
- Computer Vision and Pattern Recognition 61
- Environmental Engineering 54
- Immunology 54
Countries citing papers authored by Monther Alhamdoosh
This map shows the geographic impact of Monther Alhamdoosh'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 Monther Alhamdoosh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Monther Alhamdoosh more than expected).
Fields of papers citing papers by Monther Alhamdoosh
This network shows the impact of papers produced by Monther Alhamdoosh. 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 Monther Alhamdoosh. The network helps show where Monther Alhamdoosh may publish in the future.
Co-authorship network of co-authors of Monther Alhamdoosh
This figure shows the co-authorship network connecting the top 25 collaborators of Monther Alhamdoosh. A scholar is included among the top collaborators of Monther Alhamdoosh 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 Monther Alhamdoosh. Monther Alhamdoosh is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 2 | |
| 3 | 2 | |
| 4 | 6 | |
| 5 | 11 | |
| 6 | 16 | |
| 7 | 2 | |
| 8 | 26 | |
| 9 | 10 | |
| 10 | 32 | |
| 11 | 10 | |
| 12 | 120 | |
| 13 | 8 | |
| 14 | 54 | |
| 15 | 154 | |
| 16 | 79 | |
| 17 | 1 | |
| 18 | 30 |
About Monther Alhamdoosh
Monther Alhamdoosh is a scholar working on Immunology, Neurology and Dermatology, having authored 18 papers that have together received 563 indexed citations. Recurring topics across this work include Machine Learning and ELM (3 papers), Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis (2 papers) and Machine Learning in Bioinformatics (2 papers). The work is most often cited by research in Artificial Intelligence (179 citations), Environmental Engineering (54 citations) and Computer Vision and Pattern Recognition (61 citations). Monther Alhamdoosh has collaborated with scholars based in Australia, Switzerland and United Kingdom. Frequent co-authors include Dianhui Wang, Milica Ng, Nicholas J. Wilson, Matthew E. Ritchie, Michael J. Wilson, Julie M. Sheridan, Huy Huynh, D. Gabriëls, Muhammed Khlosi and Ahmed Douaik. Their work appears in journals such as Circulation, SHILAP Revista de lepidopterología and Bioinformatics.
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.