Megha Bhushan
- Artificial Intelligence top 10%
- Radiology, Nuclear Medicine and Imaging top 10%
- Health Information Management top 1%
- Information Systems top 10%
- Computer Vision and Pattern Recognition top 10%
- Co-authors
- Meghavi RanaShivani GoelPiyush SamantAshok KumarAjay KumarKaramjit KaurKanupriya VermaGia Nhu Nguyen
- Topics
- Artificial Intelligence in Healthcare (8 papers)Advanced Software Engineering Methodologies (8 papers)Software Engineering Research (6 papers)
In The Last Decade
Megha Bhushan
35 papers receiving 470 citations
Hit Papers
Peers
Comparison fields: 5 of 103
- Artificial Intelligence 200
- Radiology, Nuclear Medicine and Imaging 135
- Health Information Management 112
- Information Systems 74
- Computer Vision and Pattern Recognition 65
Countries citing papers authored by Megha Bhushan
This map shows the geographic impact of Megha Bhushan'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 Megha Bhushan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Megha Bhushan more than expected).
Fields of papers citing papers by Megha Bhushan
This network shows the impact of papers produced by Megha Bhushan. 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 Megha Bhushan. The network helps show where Megha Bhushan may publish in the future.
Co-authorship network of co-authors of Megha Bhushan
This figure shows the co-authorship network connecting the top 25 collaborators of Megha Bhushan. A scholar is included among the top collaborators of Megha Bhushan 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 Megha Bhushan. Megha Bhushan 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 | 11 | |
| 6 | 28 | |
| 7 | 3 | |
| 8 | 1 | |
| 9 | 2 | |
| 10 | 2 | |
| 11 | Machine learning and deep learning approach for medical image analysis: diagnosis to detectionbreakdown → | 158 |
| 12 | 9 | |
| 13 | 16 | |
| 14 | 23 | |
| 15 | 9 | |
| 16 | 12 | |
| 17 | 16 | |
| 18 | 4 | |
| 19 | 17 | |
| 20 | Optimization of segment size assuring application perceived QoS in healthcare | 7 |
About Megha Bhushan
Megha Bhushan is a scholar working on Medical Laboratory Technology, Health Information Management and Computer Science Applications, having authored 39 papers that have together received 488 indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare (8 papers), Advanced Software Engineering Methodologies (8 papers) and Software Engineering Research (6 papers). The work is most often cited by research in Health Information Management (112 citations), Medical Laboratory Technology (22 citations) and Health Informatics (14 citations). Megha Bhushan has collaborated with scholars based in India and Spain. Frequent co-authors include Meghavi Rana, Shivani Goel, Piyush Samant, Ashok Kumar, Ajay Kumar, Karamjit Kaur, Kanupriya Verma, Gia Nhu Nguyen, Biswajit Mondal and Monika Mangla. Their work appears in journals such as Expert Systems with Applications, Neural Computing and Applications and Artificial Intelligence Review.
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.