Saqib Ejaz Awan
Impact in
- Health Informatics top 5%
- Artificial Intelligence in Healthcare and Education
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- Artificial Intelligence in Healthcare
Papers in
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- Artificial Intelligence in Healthcare 4
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- Cardiac Ischemia and Reperfusion 2
- Co-authors
- Ferdous Sohel (5 shared papers)Frank Sanfilippo (5 shared papers)Mohammed Bennamoun (5 shared papers)Girish Dwivedi (5 shared papers)Benjamin J.W. Chow (1 shared paper)Benedikt Preckel (2 shared papers)Octavian Toma (1 shared paper)Nina C. Weber (2 shared papers)
- Journals
- Anesthesiology (2 papers)Neural Computing and Applications (1 paper)Current Opinion in Cardiology (1 paper)PLoS ONE (1 paper)ESC Heart Failure (1 paper)
- Partner nations
- AustraliaUnited StatesSpain
In The Last Decade
Saqib Ejaz Awan
7 papers receiving 248 citations
Peers
Comparison fields: 5 of 78
- Health Informatics 24
- Health Information Management 80
- Cardiology and Cardiovascular Medicine 106
- Developmental Neuroscience 18
- Artificial Intelligence 90
Countries citing papers authored by Saqib Ejaz Awan
This map shows the geographic impact of Saqib Ejaz Awan'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 Saqib Ejaz Awan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Saqib Ejaz Awan more than expected).
Fields of papers citing papers by Saqib Ejaz Awan
This network shows the impact of papers produced by Saqib Ejaz Awan. 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 Saqib Ejaz Awan. The network helps show where Saqib Ejaz Awan may publish in the future.
Co-authors
The 14 scholars most cited alongside Saqib Ejaz Awan, 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 | 2019 | 90 | |
| 2 | 2017 | 74 | |
| 3 | 2019 | 48 | |
| 4 | 2005 | 22 | |
| 5 | 2022 | 20 | |
| 6 | 2005 | 1 | |
| 7 | 2016 | 1 | |
| 8 | Machine learning in heart failure | 2017 | 0 |
About Saqib Ejaz Awan
Saqib Ejaz Awan is a scholar working on Health Information Management, Pathology and Forensic Medicine, Cardiology and Cardiovascular Medicine, Cognitive Neuroscience and Artificial Intelligence, having authored 8 papers that have together received 256 indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare (4 papers), Heart Failure Treatment and Management (2 papers), Cardiac Ischemia and Reperfusion (2 papers), Nitric Oxide and Endothelin Effects (2 papers), Machine Learning in Healthcare (2 papers), Mental Health Research Topics (1 paper), Statistical Methods and Bayesian Inference (1 paper) and EEG and Brain-Computer Interfaces (1 paper). The work is most often cited by research in Health Informatics (24 citations), Health Information Management (80 citations), Cardiology and Cardiovascular Medicine (106 citations), Developmental Neuroscience (18 citations) and Artificial Intelligence (90 citations). Saqib Ejaz Awan has collaborated with scholars based in Australia, United States and Spain. Frequent co-authors include Ferdous Sohel, Frank Sanfilippo, Mohammed Bennamoun, Girish Dwivedi, Benjamin J.W. Chow, Benedikt Preckel, Octavian Toma, Nina C. Weber, Jan Fräßdorf and W. Schlack. Their work appears in journals such as Anesthesiology, Neural Computing and Applications, Current Opinion in Cardiology, PLoS ONE and ESC Heart Failure.
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.