Seema Shah
- Artificial Intelligence top 10%
- Computer Networks and Communications top 10%
- Computer Vision and Pattern Recognition top 10%
- Public Health, Environmental and Occupational Health
- Electrical and Electronic Engineering
- Topics
- Anomaly Detection Techniques and Applications (4 papers)Internet Traffic Analysis and Secure E-voting (3 papers)Network Security and Intrusion Detection (3 papers)
- Journals
- The Journal of PediatricsTransactions of the Royal Society of Tropical Medicine and HygieneJournal of Network and Computer Applications
- Partner nations
- IndiaUnited States
In The Last Decade
Seema Shah
10 papers receiving 508 citations
Hit Papers
Peers
Comparison fields: 5 of 132
- Artificial Intelligence 171
- Computer Networks and Communications 65
- Computer Vision and Pattern Recognition 62
- Public Health, Environmental and Occupational Health 52
- Electrical and Electronic Engineering 49
Countries citing papers authored by Seema Shah
This map shows the geographic impact of Seema 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 Seema Shah with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Seema Shah more than expected).
Fields of papers citing papers by Seema Shah
This network shows the impact of papers produced by Seema 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 Seema Shah. The network helps show where Seema Shah may publish in the future.
Co-authorship network of co-authors of Seema Shah
This figure shows the co-authorship network connecting the top 25 collaborators of Seema Shah. A scholar is included among the top collaborators of Seema Shah 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 Seema Shah. Seema Shah is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 22 | |
| 2 | 13 | |
| 3 | 4 | |
| 4 | A Review of Machine Learning and Deep Learning Applicationsbreakdown → | 416 |
| 5 | 2 | |
| 6 | 2 | |
| 7 | 16 | |
| 8 | An Expert System For Hepatitis B Diagnosis Using Artificial Neural Networks | 1 |
| 9 | Thrombocytopenia In P. Vivax Malaria | 6 |
| 10 | 8 | |
| 11 | 45 |
About Seema Shah
Seema Shah is a scholar working on Health Information Management, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 11 papers that have together received 535 indexed citations. Recurring topics across this work include Anomaly Detection Techniques and Applications (4 papers), Internet Traffic Analysis and Secure E-voting (3 papers) and Network Security and Intrusion Detection (3 papers). The work is most often cited by research in Health Informatics (12 citations), Artificial Intelligence (171 citations) and Health Information Management (19 citations). Seema Shah has collaborated with scholars based in India and United States. Frequent co-authors include Sanjeev Sharma, K. C. Das, Kanjaksha Ghosh, G. Garewal, Neelam Marwaha, D. Mohanty, Bo Jin, Zhou Tan, John T. Kanegaye and Harvey J. Cohen. Their work appears in journals such as The Journal of Pediatrics, Transactions of the Royal Society of Tropical Medicine and Hygiene and Journal of Network and Computer Applications.
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.