Shazia Akbar
Impact in
- Biophysics top 5%
- Cell Image Analysis Techniques
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- Radiomics and Machine Learning in Medical Imaging
Papers in
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- AI in cancer detection 10
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- Medical Image Segmentation Techniques 4
- Image Retrieval and Classification Techniques 3
- Co-authors
- S.J. McKenna (10 shared papers)Siyamalan Manivannan (5 shared papers)Jianguo Zhang (5 shared papers)Wenqi Li (5 shared papers)Anne L. Martel (5 shared papers)Sharon Nofech‐Mozes (5 shared papers)Ruixuan Wang (2 shared papers)Sherine Salama (4 shared papers)
- Journals
- Journal of Clinical Oncology (2 papers)JCO Clinical Cancer Informatics (1 paper)Pattern Recognition (1 paper)Scientific Reports (1 paper)Journal of Pathology Informatics (1 paper)
- Partner nations
- United KingdomCanadaUnited States
In The Last Decade
Shazia Akbar
19 papers receiving 309 citations
Peers
Comparison fields: 5 of 53
- Biophysics 57
- Radiology, Nuclear Medicine and Imaging 123
- Computer Vision and Pattern Recognition 127
- Media Technology 48
- Artificial Intelligence 175
Countries citing papers authored by Shazia Akbar
This map shows the geographic impact of Shazia Akbar'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 Shazia Akbar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shazia Akbar more than expected).
Fields of papers citing papers by Shazia Akbar
This network shows the impact of papers produced by Shazia Akbar. 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 Shazia Akbar. The network helps show where Shazia Akbar may publish in the future.
Co-authors
The 25 scholars most cited alongside Shazia Akbar, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 65 | |
| 2 | 2016 | 51 | |
| 3 | 2019 | 42 | |
| 4 | 2015 | 31 | |
| 5 | 2021 | 23 | |
| 6 | 2014 | 20 | |
| 7 | 2013 | 16 | |
| 8 | 2018 | 15 | |
| 9 | 2021 | 8 | |
| 10 | 2019 | 8 | |
| 11 | 2018 | 8 | |
| 12 | 2014 | 6 | |
| 13 | 2015 | 6 | |
| 14 | Tumour segmentation in breast tissue microarray images using spin-context | 2012 | 4 |
| 15 | 2016 | 4 | |
| 16 | 2014 | 3 | |
| 17 | 2022 | 3 | |
| 18 | 2021 | 1 | |
| 19 | Spin-context Segmentation of Breast Tissue Microarray Images | 2013 | 1 |
| 20 | 2023 | 0 |
About Shazia Akbar
Shazia Akbar is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Molecular Biology and Biophysics, having authored 21 papers that have together received 315 indexed citations. Recurring topics across this work include AI in cancer detection (10 papers), Radiomics and Machine Learning in Medical Imaging (5 papers), Medical Image Segmentation Techniques (4 papers), Image Retrieval and Classification Techniques (3 papers), Cell Image Analysis Techniques (3 papers), Head and Neck Cancer Studies (2 papers), Gene expression and cancer classification (2 papers) and Image Processing Techniques and Applications (2 papers). The work is most often cited by research in Biophysics (57 citations), Radiology, Nuclear Medicine and Imaging (123 citations), Computer Vision and Pattern Recognition (127 citations), Media Technology (48 citations) and Artificial Intelligence (175 citations). Shazia Akbar has collaborated with scholars based in United Kingdom, Canada and United States. Frequent co-authors include S.J. McKenna, Siyamalan Manivannan, Jianguo Zhang, Wenqi Li, Anne L. Martel, Sharon Nofech‐Mozes, Ruixuan Wang, Sherine Salama, Lee B. Jordan and Emanuele Trucco. Their work appears in journals such as Journal of Clinical Oncology, JCO Clinical Cancer Informatics, Pattern Recognition, Scientific Reports and Journal of Pathology Informatics.
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.