Abir Hussain
- Health Information Management top 0.5%
- Artificial Intelligence in Healthcare 6
- Health Informatics top 5%
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- Online Learning and Analytics 4
- Gastroenterology top 5%
- Artificial Intelligence top 5%
- Imbalanced Data Classification Techniques 4
- Machine Learning in Healthcare 2
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- Neonatal and fetal brain pathology 4
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- IoT and Edge/Fog Computing 2
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- Preterm Birth and Chorioamnionitis 2
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- Gene expression and cancer classification 2
- Co-authors
- Dhiya Al‐JumeilyMohamed AlloghaniJamila MustafinaAhmed J. AljaafThar BakerPaul FergusPanos LiatsisRaghad Al-Shabandar
- Journals
- SHILAP Revista de lepidopterología (1 paper)PLoS ONE (1 paper)Monthly Notices of the Royal Astronomical Society (1 paper)
- Partner nations
- United KingdomUnited Arab EmiratesIraq
In The Last Decade
Abir Hussain
45 papers receiving 1.2k citations
Hit Papers
Peers
Comparison fields: 5 of 170
- Health Information Management 181
- Health Informatics 46
- Computer Science Applications 142
- Gastroenterology 74
- Artificial Intelligence 351
Countries citing papers authored by Abir Hussain
This map shows the geographic impact of Abir Hussain'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 Abir Hussain with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Abir Hussain more than expected).
Fields of papers citing papers by Abir Hussain
This network shows the impact of papers produced by Abir Hussain. 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 Abir Hussain. The network helps show where Abir Hussain may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Abir Hussain, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 1 | |
| 2 | 2021 | 2 | |
| 3 | 2020 | 44 | |
| 4 | 2019 | 32 | |
| 5 | 2019 | 8 | |
| 6 | A Systematic Review on Supervised and Unsupervised Machine Learning Algorithms for Data Sciencebreakdown → | 2019 | 406 |
| 7 | 2019 | 8 | |
| 8 | 2018 | 58 | |
| 9 | 2018 | 45 | |
| 10 | 2018 | 19 | |
| 11 | 2018 | 6 | |
| 12 | 2018 | 18 | |
| 13 | 2018 | 10 | |
| 14 | 2017 | 57 | |
| 15 | 2017 | 2 | |
| 16 | 2017 | 3 | |
| 17 | 2016 | 11 | |
| 18 | 2015 | 1 | |
| 19 | 2015 | 1 | |
| 20 | 2013 | 113 |
About Abir Hussain
Abir Hussain is a scholar working on Health Information Management, Computer Science Applications and Space and Planetary Science, having authored 47 papers that have together received 1.3k indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare (6 papers), Online Learning and Analytics (4 papers), Imbalanced Data Classification Techniques (4 papers), Neonatal and fetal brain pathology (4 papers), IoT and Edge/Fog Computing (2 papers), Preterm Birth and Chorioamnionitis (2 papers), Gene expression and cancer classification (2 papers) and Machine Learning in Healthcare (2 papers). The work is most often cited by research in Health Information Management (181 citations), Health Informatics (46 citations) and Computer Science Applications (142 citations). Abir Hussain has collaborated with scholars based in United Kingdom, United Arab Emirates and Iraq. Frequent co-authors include Dhiya Al‐Jumeily, Mohamed Alloghani, Jamila Mustafina, Ahmed J. Aljaaf, Thar Baker, Paul Fergus, Panos Liatsis, Raghad Al-Shabandar, Robert Keight and Haya Alaskar. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and Monthly Notices of the Royal Astronomical Society.
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.