Saqib Ejaz Awan
Impact in
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- Artificial Intelligence in Healthcare
- Health Informatics top 10%
- Artificial Intelligence in Healthcare and Education
Papers in
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- Cardiac Ischemia and Reperfusion 2
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- EEG and Brain-Computer Interfaces 1
- Co-authors
- Frank Sanfilippo (5 shared papers)Ferdous Sohel (5 shared papers)Girish Dwivedi (5 shared papers)Mohammed Bennamoun (5 shared papers)Benjamin J.W. Chow (1 shared paper)Octavian Toma (1 shared paper)W. Schlack (2 shared papers)Nina C. Weber (2 shared papers)
- Journals
- Anesthesiology (2 papers)Current Opinion in Cardiology (1 paper)ESC Heart Failure (1 paper)Neural Computing and Applications (1 paper)PLoS ONE (1 paper)
- Partner nations
- AustraliaUnited StatesSpain
In The Last Decade
Saqib Ejaz Awan
7 papers receiving 251 citations
Peers
Comparison fields: 5 of 72
- Health Information Management 68
- Health Informatics 17
- Cardiology and Cardiovascular Medicine 92
- Developmental Neuroscience 16
- Medical Laboratory Technology 4
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 | 50 | |
| 4 | 2005 | 22 | |
| 5 | 2022 | 21 | |
| 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 Pathology and Forensic Medicine, Cognitive Neuroscience, Cellular and Molecular Neuroscience, Health Information Management and Signal Processing, having authored 8 papers that have together received 259 indexed citations. Recurring topics across this work include Cardiac Ischemia and Reperfusion (2 papers), Nitric Oxide and Endothelin Effects (1 paper), Blind Source Separation Techniques (1 paper), Neuroscience and Neural Engineering (1 paper), EEG and Brain-Computer Interfaces (1 paper), Statistical Methods and Bayesian Inference (1 paper), Artificial Intelligence in Healthcare (1 paper) and Mental Health Research Topics (1 paper). The work is most often cited by research in Health Information Management (68 citations), Health Informatics (17 citations), Cardiology and Cardiovascular Medicine (92 citations), Developmental Neuroscience (16 citations) and Medical Laboratory Technology (4 citations). Saqib Ejaz Awan has collaborated with scholars based in Australia, United States and Spain. Frequent co-authors include Frank Sanfilippo, Ferdous Sohel, Girish Dwivedi, Mohammed Bennamoun, Benjamin J.W. Chow, Octavian Toma, W. Schlack, Nina C. Weber, Benedikt Preckel and Jan Fräßdorf. Their work appears in journals such as Anesthesiology, Current Opinion in Cardiology, ESC Heart Failure, Neural Computing and Applications and PLoS ONE.
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.