Dilawar Shah
Impact in
- Health Informatics top 10%
- Artificial Intelligence in Healthcare and Education
-
- COVID-19 diagnosis using AI
- Radiomics and Machine Learning in Medical Imaging
Papers in
-
- AI in cancer detection 8
- Anomaly Detection Techniques and Applications 2
- Co-authors
- Mohammad Abrar (9 shared papers)Faizan Ullah (4 shared papers)Yulin Wang (2 shared papers)Pir Masoom Shah (2 shared papers)Saif ul Islam (2 shared papers)Abdullah Gani (2 shared papers)Carsten Maple (1 shared paper)Abdu Salam (1 shared paper)
- Journals
- Scientific Reports (6 papers)International Journal of Intelligent Systems (3 papers)IEEE Access (2 papers)BMC Cardiovascular Disorders (1 paper)Science Progress (1 paper)
- Partner nations
- PakistanAfghanistanOman
In The Last Decade
Dilawar Shah
20 papers receiving 223 citations
Peers
Comparison fields: 5 of 47
- Health Informatics 13
- Radiology, Nuclear Medicine and Imaging 98
- Neurology 35
- Artificial Intelligence 90
- Signal Processing 23
Countries citing papers authored by Dilawar Shah
This map shows the geographic impact of Dilawar Shah'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 Dilawar Shah with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dilawar Shah more than expected).
Fields of papers citing papers by Dilawar Shah
This network shows the impact of papers produced by Dilawar Shah. 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 Dilawar Shah. The network helps show where Dilawar Shah may publish in the future.
Co-authors
The 25 scholars most cited alongside Dilawar Shah, 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 26 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 53 | |
| 2 | 2020 | 36 | |
| 3 | 2021 | 31 | |
| 4 | 2024 | 26 | |
| 5 | 2024 | 21 | |
| 6 | 2024 | 16 | |
| 7 | 2025 | 7 | |
| 8 | 2023 | 7 | |
| 9 | 2025 | 5 | |
| 10 | 2025 | 5 | |
| 11 | 2025 | 4 | |
| 12 | Energy constrained wireless switching | 2003 | 4 |
| 13 | 2025 | 3 | |
| 14 | 2024 | 2 | |
| 15 | 2025 | 2 | |
| 16 | Partition-based Face Recognition Using LDP and SVM | 2017 | 2 |
| 17 | 2025 | 1 | |
| 18 | DIAGNOSTIC YEILD OF PLEURAL BIOPSY IN EXUDATIVE PLEURAL EFFUSION | 2011 | 1 |
| 19 | 2024 | 1 | |
| 20 | 2018 | 1 |
About Dilawar Shah
Dilawar Shah is a scholar working on Artificial Intelligence, Computer Networks and Communications, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Molecular Biology, having authored 26 papers that have together received 228 indexed citations. Recurring topics across this work include AI in cancer detection (8 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), Brain Tumor Detection and Classification (2 papers), Cutaneous Melanoma Detection and Management (2 papers), Context-Aware Activity Recognition Systems (2 papers), Anomaly Detection Techniques and Applications (2 papers), Wireless Body Area Networks (2 papers) and COVID-19 diagnosis using AI (2 papers). The work is most often cited by research in Health Informatics (13 citations), Radiology, Nuclear Medicine and Imaging (98 citations), Neurology (35 citations), Artificial Intelligence (90 citations) and Signal Processing (23 citations). Dilawar Shah has collaborated with scholars based in Pakistan, Afghanistan and Oman. Frequent co-authors include Mohammad Abrar, Faizan Ullah, Yulin Wang, Pir Masoom Shah, Saif ul Islam, Abdullah Gani, Carsten Maple, Abdu Salam, Masood Ahmad and Nadeem Sarwar. Their work appears in journals such as Scientific Reports, International Journal of Intelligent Systems, IEEE Access, BMC Cardiovascular Disorders and Science Progress.
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.