Akshay Jain
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition
- General Health Professions
- Health Information Management top 5%
- Cardiology and Cardiovascular Medicine
- Co-authors
- Bhumika GuptaJames M. KellerMihail PopescuMohit BansalRichelle J. KoopmanVictoria A. ShafferShannon M. CanfieldPete Wegier
- Topics
- Blood Pressure and Hypertension Studies (4 papers)Context-Aware Activity Recognition Systems (3 papers)Time Series Analysis and Forecasting (2 papers)
- Cited by
- Health Information ManagementArtificial IntelligenceComputer Vision and Pattern Recognition
- Journals
- Journal of Medical Internet ResearchMedical Decision MakingJournal of Biomedical Informatics
- Partner nations
- United StatesCanada
In The Last Decade
Akshay Jain
13 papers receiving 259 citations
Peers
Comparison fields: 5 of 98
- Artificial Intelligence 92
- Computer Vision and Pattern Recognition 56
- General Health Professions 32
- Health Information Management 29
- Cardiology and Cardiovascular Medicine 25
Countries citing papers authored by Akshay Jain
This map shows the geographic impact of Akshay Jain'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 Akshay Jain with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Akshay Jain more than expected).
Fields of papers citing papers by Akshay Jain
This network shows the impact of papers produced by Akshay Jain. 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 Akshay Jain. The network helps show where Akshay Jain may publish in the future.
Co-authorship network of co-authors of Akshay Jain
This figure shows the co-authorship network connecting the top 25 collaborators of Akshay Jain. A scholar is included among the top collaborators of Akshay Jain 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 Akshay Jain. Akshay Jain is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 10 | |
| 2 | 6 | |
| 3 | 28 | |
| 4 | 27 | |
| 5 | 21 | |
| 6 | 3 | |
| 7 | 2 | |
| 8 | 10 | |
| 9 | 2 | |
| 10 | 135 | |
| 11 | 5 | |
| 12 | 8 | |
| 13 | 11 |
About Akshay Jain
Akshay Jain is a scholar working on Applied Psychology, Signal Processing and Computer Vision and Pattern Recognition, having authored 13 papers that have together received 268 indexed citations. Recurring topics across this work include Blood Pressure and Hypertension Studies (4 papers), Context-Aware Activity Recognition Systems (3 papers) and Time Series Analysis and Forecasting (2 papers). The work is most often cited by research in Health Information Management (29 citations), Artificial Intelligence (92 citations) and Computer Vision and Pattern Recognition (56 citations). Akshay Jain has collaborated with scholars based in United States and Canada. Frequent co-authors include Bhumika Gupta, James M. Keller, Mihail Popescu, Mohit Bansal, Richelle J. Koopman, Victoria A. Shaffer, Shannon M. Canfield, Pete Wegier, Jeffery L. Belden and Linsey M. Steege. Their work appears in journals such as Journal of Medical Internet Research, Medical Decision Making and Journal of Biomedical Informatics.
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.