Anabia Sohail
- Artificial Intelligence top 5%
- Radiology, Nuclear Medicine and Imaging top 5%
- Computer Vision and Pattern Recognition top 5%
- Environmental Engineering top 10%
- Biophysics top 5%
- Co-authors
- Asifullah KhanSaddam Hussain KhanZunaira RaufKunio WatanabeAbdul Rehman KhanAneela ZameerE.U. KhanNoorul Wahab
- Topics
- AI in cancer detection (12 papers)COVID-19 diagnosis using AI (10 papers)Digital Imaging for Blood Diseases (8 papers)
- Partner nations
- PakistanSouth KoreaUnited Arab Emirates
In The Last Decade
Anabia Sohail
20 papers receiving 712 citations
Hit Papers
Peers
Comparison fields: 5 of 102
- Artificial Intelligence 320
- Radiology, Nuclear Medicine and Imaging 290
- Computer Vision and Pattern Recognition 204
- Environmental Engineering 91
- Biophysics 73
Countries citing papers authored by Anabia Sohail
This map shows the geographic impact of Anabia Sohail'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 Anabia Sohail with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Anabia Sohail more than expected).
Fields of papers citing papers by Anabia Sohail
This network shows the impact of papers produced by Anabia Sohail. 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 Anabia Sohail. The network helps show where Anabia Sohail may publish in the future.
Co-authorship network of co-authors of Anabia Sohail
This figure shows the co-authorship network connecting the top 25 collaborators of Anabia Sohail. A scholar is included among the top collaborators of Anabia Sohail 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 Anabia Sohail. Anabia Sohail 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 | 0 | |
| 3 | 0 | |
| 4 | 9 | |
| 5 | A survey of the vision transformers and their CNN-transformer based variantsbreakdown → | 148 |
| 6 | 32 | |
| 7 | 8 | |
| 8 | 4 | |
| 9 | 53 | |
| 10 | 5 | |
| 11 | 65 | |
| 12 | 25 | |
| 13 | 53 | |
| 14 | 51 | |
| 15 | 75 | |
| 16 | 13 | |
| 17 | 23 | |
| 18 | 44 | |
| 19 | 74 | |
| 20 | 21 |
About Anabia Sohail
Anabia Sohail is a scholar working on Biophysics, Radiology, Nuclear Medicine and Imaging and Computer Vision and Pattern Recognition, having authored 23 papers that have together received 732 indexed citations. Recurring topics across this work include AI in cancer detection (12 papers), COVID-19 diagnosis using AI (10 papers) and Digital Imaging for Blood Diseases (8 papers). The work is most often cited by research in Health Informatics (25 citations), Biophysics (73 citations) and Radiology, Nuclear Medicine and Imaging (290 citations). Anabia Sohail has collaborated with scholars based in Pakistan, South Korea and United Arab Emirates. Frequent co-authors include Asifullah Khan, Saddam Hussain Khan, Zunaira Rauf, Kunio Watanabe, Abdul Rehman Khan, Aneela Zameer, E.U. Khan, Noorul Wahab, Yousry Mahmoud Ghazaw and Abdul Razzaq Ghumman. Their work appears in journals such as Scientific Reports, IEEE Access and Medical Image Analysis.
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.