Deepta Rajan
Impact in
- Health Informatics top 5%
- Artificial Intelligence in Healthcare and Education
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- Artificial Intelligence in Healthcare
Papers in
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- Machine Learning in Healthcare 5
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- COVID-19 diagnosis using AI 5
- Radiomics and Machine Learning in Medical Imaging 3
- Co-authors
- Jayaraman J. Thiagarajan (10 shared papers)Andreas Spanias (9 shared papers)Huan Song (1 shared paper)David Beymer (4 shared papers)Pavan Turaga (1 shared paper)Mahesh K. Banavar (5 shared papers)Michal Rosen‐Zvi (2 shared papers)Deddeh Ballah (2 shared papers)
- Journals
- Scientific Reports (2 papers)Patterns (2 papers)International Journal of Artificial Intelligence Tools (1 paper)arXiv (Cornell University) (2 papers)Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)
- Partner nations
- United StatesSwitzerlandIndia
In The Last Decade
Deepta Rajan
18 papers receiving 386 citations
Deepta Rajan's Hit Papers
Peers
Comparison fields: 5 of 87
- Health Informatics 39
- Health Information Management 64
- Signal Processing 96
- Artificial Intelligence 213
- Management Science and Operations Research 43
Countries citing papers authored by Deepta Rajan
This map shows the geographic impact of Deepta Rajan'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 Deepta Rajan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Deepta Rajan more than expected).
Fields of papers citing papers by Deepta Rajan
This network shows the impact of papers produced by Deepta Rajan. 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 Deepta Rajan. The network helps show where Deepta Rajan may publish in the future.
Co-authors
The 25 scholars most cited alongside Deepta Rajan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Attend and Diagnose: Clinical Time Series Analysis Using Attention Models Hit paper breakdown → | 2018 | 264 |
| 2 | 2021 | 38 | |
| 3 | 2022 | 20 | |
| 4 | 2013 | 13 | |
| 5 | 2020 | 11 | |
| 6 | 2021 | 11 | |
| 7 | 2014 | 11 | |
| 8 | 2018 | 8 | |
| 9 | 2014 | 6 | |
| 10 | 2012 | 3 | |
| 11 | 2013 | 3 | |
| 12 | Fair Selective Classification Via Sufficiency | 2021 | 3 |
| 13 | Self-Training with Improved Regularization for Few-Shot Chest X-Ray Classification. | 2020 | 2 |
| 14 | Automatic Diagnosis of Pulmonary Embolism Using an Attention-guided Framework: A Large-scale Study | 2020 | 2 |
| 15 | 2020 | 2 | |
| 16 | Can Deep Clinical Models Handle Real-World Domain Shifts? | 2018 | 1 |
| 17 | Interactive Signal Processing Education Applications for the Android Platform | 2019 | 1 |
| 18 | 2023 | 1 | |
| 19 | 2025 | 0 |
About Deepta Rajan
Deepta Rajan is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Cardiology and Cardiovascular Medicine, Information Systems and Computer Vision and Pattern Recognition, having authored 19 papers that have together received 400 indexed citations. Recurring topics across this work include COVID-19 diagnosis using AI (5 papers), Machine Learning in Healthcare (5 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), ECG Monitoring and Analysis (3 papers), Interactive and Immersive Displays (2 papers), Experimental Learning in Engineering (2 papers), Medical Image Segmentation Techniques (2 papers) and EEG and Brain-Computer Interfaces (2 papers). The work is most often cited by research in Health Informatics (39 citations), Health Information Management (64 citations), Signal Processing (96 citations), Artificial Intelligence (213 citations) and Management Science and Operations Research (43 citations). Deepta Rajan has collaborated with scholars based in United States, Switzerland and India. Frequent co-authors include Jayaraman J. Thiagarajan, Andreas Spanias, Huan Song, David Beymer, Pavan Turaga, Mahesh K. Banavar, Michal Rosen‐Zvi, Deddeh Ballah, Michal Guindy and Karthikeyan Natesan Ramamurthy. Their work appears in journals such as Scientific Reports, Patterns, International Journal of Artificial Intelligence Tools, arXiv (Cornell University) and Proceedings of the AAAI Conference on Artificial Intelligence.
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.