Talha Qaiser
Impact in
- Biophysics top 10%
- Cell Image Analysis Techniques
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- Radiomics and Machine Learning in Medical Imaging
Papers in
-
- AI in cancer detection 10
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- Digital Imaging for Blood Diseases 5
- Medical Image Segmentation Techniques 1
- Co-authors
- Nasir Rajpoot (12 shared papers)Yee‐Wah Tsang (2 shared papers)Naoufel Werghi (3 shared papers)Arif Mahmood (3 shared papers)Sajid Javed (3 shared papers)Simon Graham (2 shared papers)Korsuk Sirinukunwattana (1 shared paper)Kazuaki Nakane (1 shared paper)
- Journals
- Medical Image Analysis (3 papers)Computerized Medical Imaging and Graphics (1 paper)Computers in Biology and Medicine (1 paper)Oncotarget (1 paper)Journal of Clinical Oncology (1 paper)
- Partner nations
- United KingdomPakistanUnited Arab Emirates
In The Last Decade
Talha Qaiser
16 papers receiving 195 citations
Peers
Comparison fields: 5 of 35
- Biophysics 29
- Radiology, Nuclear Medicine and Imaging 82
- Computer Vision and Pattern Recognition 82
- Artificial Intelligence 124
- Health Informatics 4
Countries citing papers authored by Talha Qaiser
This map shows the geographic impact of Talha Qaiser'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 Talha Qaiser with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Talha Qaiser more than expected).
Fields of papers citing papers by Talha Qaiser
This network shows the impact of papers produced by Talha Qaiser. 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 Talha Qaiser. The network helps show where Talha Qaiser may publish in the future.
Co-authors
The 25 scholars most cited alongside Talha Qaiser, 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 | 2016 | 46 | |
| 2 | 2022 | 23 | |
| 3 | 2018 | 23 | |
| 4 | 2018 | 20 | |
| 5 | 2023 | 15 | |
| 6 | 2023 | 14 | |
| 7 | 2017 | 14 | |
| 8 | 2017 | 11 | |
| 9 | 2024 | 7 | |
| 10 | 2017 | 5 | |
| 11 | 2019 | 5 | |
| 12 | 2021 | 4 | |
| 13 | 2024 | 4 | |
| 14 | 2022 | 3 | |
| 15 | 2019 | 1 | |
| 16 | 2025 | 1 | |
| 17 | 2025 | 0 | |
| 18 | 2025 | 0 |
About Talha Qaiser
Talha Qaiser is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Biophysics and Computational Theory and Mathematics, having authored 18 papers that have together received 196 indexed citations. Recurring topics across this work include AI in cancer detection (10 papers), Radiomics and Machine Learning in Medical Imaging (6 papers), Digital Imaging for Blood Diseases (5 papers), Cell Image Analysis Techniques (5 papers), Topological and Geometric Data Analysis (3 papers), Multiple Myeloma Research and Treatments (2 papers), Gene expression and cancer classification (1 paper) and Medical Image Segmentation Techniques (1 paper). The work is most often cited by research in Biophysics (29 citations), Radiology, Nuclear Medicine and Imaging (82 citations), Computer Vision and Pattern Recognition (82 citations), Artificial Intelligence (124 citations) and Health Informatics (4 citations). Talha Qaiser has collaborated with scholars based in United Kingdom, Pakistan and United Arab Emirates. Frequent co-authors include Nasir Rajpoot, Yee‐Wah Tsang, Naoufel Werghi, Arif Mahmood, Sajid Javed, Simon Graham, Korsuk Sirinukunwattana, Kazuaki Nakane, Raja Muhammad Saad Bashir and Syed Ali Khurram. Their work appears in journals such as Medical Image Analysis, Computerized Medical Imaging and Graphics, Computers in Biology and Medicine, Oncotarget and Journal of Clinical Oncology.
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.