Anees Kazi
- Artificial Intelligence
- Computer Vision and Pattern Recognition
- Radiology, Nuclear Medicine and Imaging
- Health Informatics top 5%
- Biomedical Engineering
- Co-authors
- Nassir NavabSeyed‐Ahmad AhmadiMichael M. BronsteinLuca CosmoDiana MateusSonja KirchhoffShadi AlbarqouniPeter Biberthaler
- Topics
- Functional Brain Connectivity Studies (3 papers)Health, Environment, Cognitive Aging (3 papers)Radiomics and Machine Learning in Medical Imaging (2 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceMedical Image AnalysisHistochemistry and Cell Biology
- Partner nations
- GermanyUnited StatesUnited Kingdom
In The Last Decade
Anees Kazi
10 papers receiving 153 citations
Peers
Comparison fields: 5 of 58
- Artificial Intelligence 57
- Computer Vision and Pattern Recognition 41
- Radiology, Nuclear Medicine and Imaging 34
- Health Informatics 25
- Biomedical Engineering 19
Countries citing papers authored by Anees Kazi
This map shows the geographic impact of Anees Kazi'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 Anees Kazi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Anees Kazi more than expected).
Fields of papers citing papers by Anees Kazi
This network shows the impact of papers produced by Anees Kazi. 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 Anees Kazi. The network helps show where Anees Kazi may publish in the future.
Co-authorship network of co-authors of Anees Kazi
This figure shows the co-authorship network connecting the top 25 collaborators of Anees Kazi. A scholar is included among the top collaborators of Anees Kazi 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 Anees Kazi. Anees Kazi 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 | 17 | |
| 3 | 2 | |
| 4 | 5 | |
| 5 | 61 | |
| 6 | 1 | |
| 7 | 2 | |
| 8 | 10 | |
| 9 | 34 | |
| 10 | 11 | |
| 11 | 1 | |
| 12 | 12 |
About Anees Kazi
Anees Kazi is a scholar working on Health Informatics, Health, Toxicology and Mutagenesis and Health Information Management, having authored 12 papers that have together received 156 indexed citations. Recurring topics across this work include Functional Brain Connectivity Studies (3 papers), Health, Environment, Cognitive Aging (3 papers) and Radiomics and Machine Learning in Medical Imaging (2 papers). The work is most often cited by research in Health Informatics (25 citations), Health Information Management (11 citations) and Computer Vision and Pattern Recognition (41 citations). Anees Kazi has collaborated with scholars based in Germany, United States and United Kingdom. Frequent co-authors include Nassir Navab, Seyed‐Ahmad Ahmadi, Michael M. Bronstein, Luca Cosmo, Diana Mateus, Sonja Kirchhoff, Shadi Albarqouni, Peter Biberthaler, Chlodwig Kirchhoff and Tanveer Syeda-Mahmood. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Medical Image Analysis and Histochemistry and Cell Biology.
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.