Anas Bilal
Impact in
- Health Information Management top 0.5%
- Artificial Intelligence in Healthcare
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- Retinal Imaging and Analysis
- COVID-19 diagnosis using AI
Papers in
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- AI in cancer detection 9
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- Retinal Imaging and Analysis 13
- COVID-19 diagnosis using AI 6
- Co-authors
- Guangmin Sun (18 shared papers)Sarah Mazhar (9 shared papers)Muhammad Shafiq (10 shared papers)Haixia Long (10 shared papers)Azhar Imran (8 shared papers)Xiaowen Liu (8 shared papers)Jahanzaib Latif (5 shared papers)Liucun Zhu (1 shared paper)
- Journals
- Scientific Reports (8 papers)IEEE Access (7 papers)Frontiers in Medicine (4 papers)PLoS ONE (3 papers)Electronics (3 papers)
- Partner nations
- ChinaPakistanSaudi Arabia
In The Last Decade
Anas Bilal
57 papers receiving 1.1k citations
Anas Bilal's Hit Papers
Peers
Comparison fields: 5 of 106
- Health Information Management 231
- Radiology, Nuclear Medicine and Imaging 514
- Ophthalmology 183
- Neurology 148
- Computer Vision and Pattern Recognition 305
Countries citing papers authored by Anas Bilal
This map shows the geographic impact of Anas Bilal'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 Anas Bilal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Anas Bilal more than expected).
Fields of papers citing papers by Anas Bilal
This network shows the impact of papers produced by Anas Bilal. 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 Anas Bilal. The network helps show where Anas Bilal may publish in the future.
Co-authors
The 25 scholars most cited alongside Anas Bilal, 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 65 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | AI-Based Automatic Detection and Classification of Diabetic Retinopathy Using U-Net and Deep Learning Hit paper breakdown → | 2022 | 127 |
| 2 | 2021 | 101 | |
| 3 | 2022 | 70 | |
| 4 | NIMEQ-SACNet: A novel self-attention precision medicine model for vision-threatening diabetic retinopathy using image data Hit paper breakdown → | 2024 | 63 |
| 5 | 2024 | 56 | |
| 6 | 2022 | 54 | |
| 7 | 2023 | 50 | |
| 8 | 2021 | 45 | |
| 9 | 2022 | 42 | |
| 10 | 2020 | 41 | |
| 11 | 2021 | 37 | |
| 12 | 2024 | 35 | |
| 13 | 2021 | 32 | |
| 14 | 2023 | 28 | |
| 15 | 2021 | 27 | |
| 16 | 2025 | 21 | |
| 17 | 2023 | 21 | |
| 18 | 2025 | 19 | |
| 19 | 2024 | 17 | |
| 20 | 2025 | 17 |
About Anas Bilal
Anas Bilal is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Molecular Biology and Health Information Management, having authored 65 papers that have together received 1.2k indexed citations. Recurring topics across this work include Retinal Imaging and Analysis (13 papers), Artificial Intelligence in Healthcare (9 papers), AI in cancer detection (9 papers), Brain Tumor Detection and Classification (8 papers), Digital Imaging for Blood Diseases (7 papers), COVID-19 diagnosis using AI (6 papers), Cutaneous Melanoma Detection and Management (5 papers) and Retinal Diseases and Treatments (5 papers). The work is most often cited by research in Health Information Management (231 citations), Radiology, Nuclear Medicine and Imaging (514 citations), Ophthalmology (183 citations), Neurology (148 citations) and Computer Vision and Pattern Recognition (305 citations). Anas Bilal has collaborated with scholars based in China, Pakistan and Saudi Arabia. Frequent co-authors include Guangmin Sun, Sarah Mazhar, Muhammad Shafiq, Haixia Long, Azhar Imran, Xiaowen Liu, Jahanzaib Latif, Haixia Long, Liucun Zhu and Ning Wu. Their work appears in journals such as Scientific Reports, IEEE Access, Frontiers in Medicine, PLoS ONE and Electronics.
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.