Vivek Kumar Singh
- Artificial Intelligence top 5%
- Radiology, Nuclear Medicine and Imaging top 5%
- Computer Vision and Pattern Recognition top 5%
- Oncology
- Biomedical Engineering
- Co-authors
- Mohamed Abdel‐NasserDomènec PuigHatem A. RashwanNidhi PandeyFarhan AkramMd. Mostafa Kamal SarkerDimitris VisvikisVincent Jaouen
- Topics
- AI in cancer detection (17 papers)Radiomics and Machine Learning in Medical Imaging (12 papers)COVID-19 diagnosis using AI (4 papers)
- Journals
- SHILAP Revista de lepidopterologíaExpert Systems with ApplicationsIEEE Access
- Partner nations
- United StatesEgyptSpain
In The Last Decade
Vivek Kumar Singh
42 papers receiving 660 citations
Peers
Comparison fields: 5 of 106
- Artificial Intelligence 356
- Radiology, Nuclear Medicine and Imaging 274
- Computer Vision and Pattern Recognition 225
- Oncology 96
- Biomedical Engineering 76
Countries citing papers authored by Vivek Kumar Singh
This map shows the geographic impact of Vivek Kumar Singh'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 Vivek Kumar Singh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vivek Kumar Singh more than expected).
Fields of papers citing papers by Vivek Kumar Singh
This network shows the impact of papers produced by Vivek Kumar Singh. 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 Vivek Kumar Singh. The network helps show where Vivek Kumar Singh may publish in the future.
Co-authorship network of co-authors of Vivek Kumar Singh
This figure shows the co-authorship network connecting the top 25 collaborators of Vivek Kumar Singh. A scholar is included among the top collaborators of Vivek Kumar Singh 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 Vivek Kumar Singh. Vivek Kumar Singh 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 | 1 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 1 | |
| 7 | 1 | |
| 8 | 1 | |
| 9 | 3 | |
| 10 | 1 | |
| 11 | 43 | |
| 12 | 10 | |
| 13 | 3 | |
| 14 | 65 | |
| 15 | 45 | |
| 16 | 9 | |
| 17 | Breast Mass Segmentation and Shape Classification in Mammograms Using Deep Neural Networks. | 4 |
| 18 | 24 | |
| 19 | 48 | |
| 20 | Fast and Efficient Region Duplication Detection in Digital Images | 7 |
About Vivek Kumar Singh
Vivek Kumar Singh is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 45 papers that have together received 688 indexed citations. Recurring topics across this work include AI in cancer detection (17 papers), Radiomics and Machine Learning in Medical Imaging (12 papers) and COVID-19 diagnosis using AI (4 papers). The work is most often cited by research in Health Informatics (25 citations), Radiology, Nuclear Medicine and Imaging (274 citations) and Artificial Intelligence (356 citations). Vivek Kumar Singh has collaborated with scholars based in United States, Egypt and Spain. Frequent co-authors include Mohamed Abdel‐Nasser, Domènec Puig, Hatem A. Rashwan, Nidhi Pandey, Farhan Akram, Md. Mostafa Kamal Sarker, Dimitris Visvikis, Vincent Jaouen, Pierre-Henri Conze and Santiago Romaní. Their work appears in journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and IEEE Access.
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.