Yogan Jaya Kumar
- Artificial Intelligence top 5%
- Information Systems top 10%
- Health Information Management top 5%
- Computer Vision and Pattern Recognition
- Computer Networks and Communications
- Co-authors
- Naomie SalimAtif KhanBasit RazaZi YeMuhammad FaheemAhmad Kamran MalikJunsong WangAhmed Hamza Osman
- Topics
- Topic Modeling (18 papers)Natural Language Processing Techniques (15 papers)Advanced Text Analysis Techniques (12 papers)
In The Last Decade
Yogan Jaya Kumar
40 papers receiving 460 citations
Peers
Comparison fields: 5 of 83
- Artificial Intelligence 352
- Information Systems 74
- Health Information Management 56
- Computer Vision and Pattern Recognition 49
- Computer Networks and Communications 34
Countries citing papers authored by Yogan Jaya Kumar
This map shows the geographic impact of Yogan Jaya Kumar'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 Yogan Jaya Kumar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yogan Jaya Kumar more than expected).
Fields of papers citing papers by Yogan Jaya Kumar
This network shows the impact of papers produced by Yogan Jaya Kumar. 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 Yogan Jaya Kumar. The network helps show where Yogan Jaya Kumar may publish in the future.
Co-authorship network of co-authors of Yogan Jaya Kumar
This figure shows the co-authorship network connecting the top 25 collaborators of Yogan Jaya Kumar. A scholar is included among the top collaborators of Yogan Jaya Kumar 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 Yogan Jaya Kumar. Yogan Jaya Kumar 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 | 3 | |
| 3 | 5 | |
| 4 | 1 | |
| 5 | 3 | |
| 6 | 2 | |
| 7 | 56 | |
| 8 | Deep Echocardiography: A First Step toward Automatic Cardiac Disease Diagnosis Using Machine Learning | 3 |
| 9 | 2 | |
| 10 | 9 | |
| 11 | 1 | |
| 12 | Intelligent Conversational Bot for Interactive Marketing | 3 |
| 13 | 9 | |
| 14 | 45 | |
| 15 | 0 | |
| 16 | 82 | |
| 17 | 3 | |
| 18 | 7 | |
| 19 | 3 | |
| 20 | 14 |
About Yogan Jaya Kumar
Yogan Jaya Kumar is a scholar working on Artificial Intelligence, Medical Laboratory Technology and Management Information Systems, having authored 42 papers that have together received 497 indexed citations. Recurring topics across this work include Topic Modeling (18 papers), Natural Language Processing Techniques (15 papers) and Advanced Text Analysis Techniques (12 papers). The work is most often cited by research in Health Information Management (56 citations), Artificial Intelligence (352 citations) and Medical Laboratory Technology (10 citations). Yogan Jaya Kumar has collaborated with scholars based in Malaysia, Indonesia and Pakistan. Frequent co-authors include Naomie Salim, Atif Khan, Basit Raza, Zi Ye, Muhammad Faheem, Ahmad Kamran Malik, Junsong Wang, Ahmed Hamza Osman, Ahmad Raza Shahid and Hani Alquhayz. Their work appears in journals such as IEEE Access, Applied Soft Computing and Knowledge-Based Systems.
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.