Talha Qaiser
Impact in
-
- Cell Image Analysis Techniques
-
- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
Papers in
-
- AI in cancer detection 6
- Natural Language Processing Techniques 1
-
- Radiomics and Machine Learning in Medical Imaging 6
- Co-authors
- Nasir Rajpoot (9 shared papers)Arif Mahmood (3 shared papers)Sajid Javed (3 shared papers)Naoufel Werghi (3 shared papers)Yee‐Wah Tsang (1 shared paper)Kazuaki Nakane (1 shared paper)Korsuk Sirinukunwattana (1 shared paper)Syed Ali Khurram (1 shared paper)
- Journals
- Medical Image Analysis (3 papers)Computers in Biology and Medicine (1 paper)Journal of Clinical Oncology (1 paper)BMJ Open (1 paper)Oncotarget (1 paper)
- Partner nations
- United KingdomPakistanUnited Arab Emirates
In The Last Decade
Talha Qaiser
11 papers receiving 119 citations
Peers
Comparison fields: 5 of 33
- Biophysics 20
- Radiology, Nuclear Medicine and Imaging 55
- Computer Vision and Pattern Recognition 47
- Health Informatics 3
- Artificial Intelligence 67
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 | 39 | |
| 2 | 2018 | 21 | |
| 3 | 2022 | 20 | |
| 4 | 2023 | 13 | |
| 5 | 2023 | 11 | |
| 6 | 2024 | 5 | |
| 7 | 2017 | 5 | |
| 8 | 2022 | 3 | |
| 9 | 2024 | 1 | |
| 10 | 2025 | 1 | |
| 11 | 2019 | 1 | |
| 12 | 2025 | 0 |
About Talha Qaiser
Talha Qaiser is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Biophysics and Molecular Biology, having authored 12 papers that have together received 120 indexed citations. Recurring topics across this work include AI in cancer detection (6 papers), Radiomics and Machine Learning in Medical Imaging (6 papers), Digital Imaging for Blood Diseases (4 papers), Cell Image Analysis Techniques (3 papers), Topological and Geometric Data Analysis (2 papers), Pancreatic function and diabetes (1 paper), Natural Language Processing Techniques (1 paper) and Leprosy Research and Treatment (1 paper). The work is most often cited by research in Biophysics (20 citations), Radiology, Nuclear Medicine and Imaging (55 citations), Computer Vision and Pattern Recognition (47 citations), Health Informatics (3 citations) and Artificial Intelligence (67 citations). Talha Qaiser has collaborated with scholars based in United Kingdom, Pakistan and United Arab Emirates. Frequent co-authors include Nasir Rajpoot, Arif Mahmood, Sajid Javed, Naoufel Werghi, Yee‐Wah Tsang, Kazuaki Nakane, Korsuk Sirinukunwattana, Syed Ali Khurram, Simon Graham and Muhammad Shaban. Their work appears in journals such as Medical Image Analysis, Computers in Biology and Medicine, Journal of Clinical Oncology, BMJ Open and Oncotarget.
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.