Saad Bin Abul Kashem
- Radiology, Nuclear Medicine and Imaging top 1%
- Artificial Intelligence top 2%
- Computer Vision and Pattern Recognition top 5%
- Pulmonary and Respiratory Medicine top 10%
- Biomedical Engineering
- Co-authors
- Muhammad E. H. ChowdhuryAmith KhandakarTawsifur RahmanMohammad Tariqul IslamZaid Bin MahbubMuhammad Abdul KadirKhandaker Reajul IslamSusu M. Zughaier
- Topics
- Photovoltaic System Optimization Techniques (8 papers)COVID-19 diagnosis using AI (6 papers)Solar Radiation and Photovoltaics (5 papers)
- Partner nations
- QatarMalaysiaBangladesh
In The Last Decade
Saad Bin Abul Kashem
48 papers receiving 1.8k citations
Hit Papers
Peers
Comparison fields: 5 of 139
- Radiology, Nuclear Medicine and Imaging 1.2k
- Artificial Intelligence 756
- Computer Vision and Pattern Recognition 319
- Pulmonary and Respiratory Medicine 271
- Biomedical Engineering 124
Countries citing papers authored by Saad Bin Abul Kashem
This map shows the geographic impact of Saad Bin Abul Kashem'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 Saad Bin Abul Kashem with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Saad Bin Abul Kashem more than expected).
Fields of papers citing papers by Saad Bin Abul Kashem
This network shows the impact of papers produced by Saad Bin Abul Kashem. 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 Saad Bin Abul Kashem. The network helps show where Saad Bin Abul Kashem may publish in the future.
Co-authorship network of co-authors of Saad Bin Abul Kashem
This figure shows the co-authorship network connecting the top 25 collaborators of Saad Bin Abul Kashem. A scholar is included among the top collaborators of Saad Bin Abul Kashem 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 Saad Bin Abul Kashem. Saad Bin Abul Kashem is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 6 | |
| 4 | 10 | |
| 5 | 0 | |
| 6 | 25 | |
| 7 | 17 | |
| 8 | 6 | |
| 9 | 33 | |
| 10 | 6 | |
| 11 | 31 | |
| 12 | 0 | |
| 13 | 0 | |
| 14 | 23 | |
| 15 | Exploring the effect of image enhancement techniques on COVID-19 detection using chest X-ray imagesbreakdown → | 672 |
| 16 | 2 | |
| 17 | 4 | |
| 18 | 2 | |
| 19 | Reliable Tuberculosis Detection Using Chest X-Ray With Deep Learning, Segmentation and Visualizationbreakdown → | 375 |
| 20 | 5 |
About Saad Bin Abul Kashem
Saad Bin Abul Kashem is a scholar working on Energy Engineering and Power Technology, Industrial and Manufacturing Engineering and Renewable Energy, Sustainability and the Environment, having authored 53 papers that have together received 1.9k indexed citations. Recurring topics across this work include Photovoltaic System Optimization Techniques (8 papers), COVID-19 diagnosis using AI (6 papers) and Solar Radiation and Photovoltaics (5 papers). The work is most often cited by research in Health Informatics (106 citations), Radiology, Nuclear Medicine and Imaging (1.2k citations) and Artificial Intelligence (756 citations). Saad Bin Abul Kashem has collaborated with scholars based in Qatar, Malaysia and Bangladesh. Frequent co-authors include Muhammad E. H. Chowdhury, Amith Khandakar, Tawsifur Rahman, Mohammad Tariqul Islam, Zaid Bin Mahbub, Muhammad Abdul Kadir, Khandaker Reajul Islam, Susu M. Zughaier, Somaya Al-Máadeed and Muhammad Salman Khan. Their work appears in journals such as Scientific Reports, IEEE Access and Waste Management.
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.