Pavitra Krishnaswamy
- Cognitive Neuroscience top 10%
- Biomedical Engineering
- Radiology, Nuclear Medicine and Imaging
- Artificial Intelligence
- Psychiatry and Mental health
- Co-authors
- Hugh HerrEmery N. BrownPatrick L. PurdonJyrki AhveninenBehtash BabadiSheraz KhanMatti HämäläinenJuan Eugenio Iglesias
- Topics
- Topic Modeling (5 papers)Speech and dialogue systems (4 papers)Machine Learning in Healthcare (4 papers)
- Journals
- Proceedings of the National Academy of SciencesNeuroImagePhilosophical Transactions of the Royal Society B Biological Sciences
- Partner nations
- SingaporeUnited StatesUnited Kingdom
In The Last Decade
Pavitra Krishnaswamy
21 papers receiving 311 citations
Peers
Comparison fields: 5 of 71
- Cognitive Neuroscience 142
- Biomedical Engineering 119
- Radiology, Nuclear Medicine and Imaging 53
- Artificial Intelligence 31
- Psychiatry and Mental health 22
Countries citing papers authored by Pavitra Krishnaswamy
This map shows the geographic impact of Pavitra Krishnaswamy'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 Pavitra Krishnaswamy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pavitra Krishnaswamy more than expected).
Fields of papers citing papers by Pavitra Krishnaswamy
This network shows the impact of papers produced by Pavitra Krishnaswamy. 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 Pavitra Krishnaswamy. The network helps show where Pavitra Krishnaswamy may publish in the future.
Co-authorship network of co-authors of Pavitra Krishnaswamy
This figure shows the co-authorship network connecting the top 25 collaborators of Pavitra Krishnaswamy. A scholar is included among the top collaborators of Pavitra Krishnaswamy 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 Pavitra Krishnaswamy. Pavitra Krishnaswamy 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 | 0 | |
| 4 | 1 | |
| 5 | 1 | |
| 6 | 1 | |
| 7 | 0 | |
| 8 | 11 | |
| 9 | 11 | |
| 10 | 4 | |
| 11 | 8 | |
| 12 | A Vital Signs Telemonitoring Programme Improves the Dynamic Prediction of Readmission Risk in Patients with Heart Failure. | 3 |
| 13 | 13 | |
| 14 | 4 | |
| 15 | 103 | |
| 16 | Reference-free removal of EEG-fMRI ballistocardiogram artifacts with harmonic regression | 6 |
| 17 | 17 | |
| 18 | 8 | |
| 19 | 67 | |
| 20 | 46 |
About Pavitra Krishnaswamy
Pavitra Krishnaswamy is a scholar working on Health Informatics, Family Practice and Artificial Intelligence, having authored 23 papers that have together received 315 indexed citations. Recurring topics across this work include Topic Modeling (5 papers), Speech and dialogue systems (4 papers) and Machine Learning in Healthcare (4 papers). The work is most often cited by research in Health Informatics (17 citations), Cognitive Neuroscience (142 citations) and Biomedical Engineering (119 citations). Pavitra Krishnaswamy has collaborated with scholars based in Singapore, United States and United Kingdom. Frequent co-authors include Hugh Herr, Emery N. Brown, Patrick L. Purdon, Jyrki Ahveninen, Behtash Babadi, Sheraz Khan, Matti Hämäläinen, Juan Eugenio Iglesias, J. Markowitz and Michael Frederick Eilenberg. Their work appears in journals such as Proceedings of the National Academy of Sciences, NeuroImage and Philosophical Transactions of the Royal Society B Biological Sciences.
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.