Amanullah Asraf
Impact in
- Health Informatics top 2%
- Artificial Intelligence in Healthcare and Education
-
- COVID-19 diagnosis using AI
- Radiomics and Machine Learning in Medical Imaging
Papers in
-
- COVID-19 diagnosis using AI 4
- Radiomics and Machine Learning in Medical Imaging 2
-
- AI in cancer detection 2
- Anomaly Detection Techniques and Applications 1
- Co-authors
- Md. Zabirul Islam (3 shared papers)Md. Milon Islam (3 shared papers)Md. Rezwanul Haque (1 shared paper)Weiping Ding (1 shared paper)Ali Hassan Sodhro (1 shared paper)Mabrook Al‐Rakhami (1 shared paper)
- Journals
- SN Computer Science (1 paper)Informatics in Medicine Unlocked (1 paper)PubMed Central (1 paper)Data Archiving and Networked Services (DANS) (1 paper)
- Partner nations
- BangladeshChinaSaudi Arabia
In The Last Decade
Amanullah Asraf
4 papers receiving 586 citations
Amanullah Asraf's Hit Papers
Peers
Comparison fields: 5 of 93
- Health Informatics 55
- Radiology, Nuclear Medicine and Imaging 398
- Artificial Intelligence 291
- Health Information Management 32
- Computer Vision and Pattern Recognition 99
Countries citing papers authored by Amanullah Asraf
This map shows the geographic impact of Amanullah Asraf'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 Amanullah Asraf with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Amanullah Asraf more than expected).
Fields of papers citing papers by Amanullah Asraf
This network shows the impact of papers produced by Amanullah Asraf. 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 Amanullah Asraf. The network helps show where Amanullah Asraf may publish in the future.
Co-authors
The 6 scholars most cited alongside Amanullah Asraf, 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 | A combined deep CNN-LSTM network for the detection of novel coronavirus (COVID-19) using X-ray images Hit paper breakdown → | 2020 | 495 |
| 2 | 2020 | 67 | |
| 3 | 2022 | 28 | |
| 4 | 2021 | 12 |
About Amanullah Asraf
Amanullah Asraf is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence, Health Information Management, Pulmonary and Respiratory Medicine and Computer Vision and Pattern Recognition, having authored 4 papers that have together received 602 indexed citations. Recurring topics across this work include COVID-19 diagnosis using AI (4 papers), Radiomics and Machine Learning in Medical Imaging (2 papers), AI in cancer detection (2 papers), Artificial Intelligence in Healthcare (1 paper), Digital Imaging for Blood Diseases (1 paper), Lung Cancer Diagnosis and Treatment (1 paper) and Anomaly Detection Techniques and Applications (1 paper). The work is most often cited by research in Health Informatics (55 citations), Radiology, Nuclear Medicine and Imaging (398 citations), Artificial Intelligence (291 citations), Health Information Management (32 citations) and Computer Vision and Pattern Recognition (99 citations). Amanullah Asraf has collaborated with scholars based in Bangladesh, China and Saudi Arabia. Frequent co-authors include Md. Zabirul Islam, Md. Milon Islam, Md. Rezwanul Haque, Weiping Ding, Ali Hassan Sodhro and Mabrook Al‐Rakhami. Their work appears in journals such as SN Computer Science, Informatics in Medicine Unlocked, PubMed Central and Data Archiving and Networked Services (DANS).
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.