Faisal Farooq
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 5%
- Signal Processing top 5%
- Information Systems top 5%
- Cardiology and Cardiovascular Medicine
- Co-authors
- Venu GovindarajuRuud M. BolleNalini RathaGlenn FungMichael PerroneJalal AhmedLihong ZhengShipeng Yu
- Topics
- Handwritten Text Recognition Techniques (8 papers)Natural Language Processing Techniques (7 papers)Artificial Intelligence in Healthcare (5 papers)
- Partner nations
- United StatesQatarDenmark
In The Last Decade
Faisal Farooq
43 papers receiving 711 citations
Peers
Comparison fields: 5 of 107
- Computer Vision and Pattern Recognition 330
- Artificial Intelligence 223
- Signal Processing 202
- Information Systems 153
- Cardiology and Cardiovascular Medicine 77
Countries citing papers authored by Faisal Farooq
This map shows the geographic impact of Faisal Farooq'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 Faisal Farooq with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Faisal Farooq more than expected).
Fields of papers citing papers by Faisal Farooq
This network shows the impact of papers produced by Faisal Farooq. 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 Faisal Farooq. The network helps show where Faisal Farooq may publish in the future.
Co-authorship network of co-authors of Faisal Farooq
This figure shows the co-authorship network connecting the top 25 collaborators of Faisal Farooq. A scholar is included among the top collaborators of Faisal Farooq 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 Faisal Farooq. Faisal Farooq 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 | 3 | |
| 4 | 2 | |
| 5 | 23 | |
| 6 | 3 | |
| 7 | 3 | |
| 8 | 50 | |
| 9 | 2 | |
| 10 | 26 | |
| 11 | 3 | |
| 12 | 41 | |
| 13 | 57 | |
| 14 | 75 | |
| 15 | Categorizing medications from unstructured clinical notes. | 1 |
| 16 | Active Learning from Multiple Knowledge Sources | 27 |
| 17 | Building Hospital-Specific Readmission Risk Prediction Models for Heart Failure, Acute Myocardial Infarction and Pneumonia patients. | 2 |
| 18 | 17 | |
| 19 | 0 | |
| 20 | 2 |
About Faisal Farooq
Faisal Farooq is a scholar working on Health Information Management, Signal Processing and Health Informatics, having authored 45 papers that have together received 753 indexed citations. Recurring topics across this work include Handwritten Text Recognition Techniques (8 papers), Natural Language Processing Techniques (7 papers) and Artificial Intelligence in Healthcare (5 papers). The work is most often cited by research in Signal Processing (202 citations), Computer Vision and Pattern Recognition (330 citations) and Health Informatics (21 citations). Faisal Farooq has collaborated with scholars based in United States, Qatar and Denmark. Frequent co-authors include Venu Govindaraju, Ruud M. Bolle, Nalini Ratha, Glenn Fung, Michael Perrone, Jalal Ahmed, Lihong Zheng, Shipeng Yu, Balaji Krishnapuram and Sergey Tulyakov. Their work appears in journals such as Neuron, Pattern Recognition and Journal of Medical Internet Research.
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.