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
- AI in cancer detection 3
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- COVID-19 diagnosis using AI 5
- Radiomics and Machine Learning in Medical Imaging 5
- Co-authors
- Jayaraman J. Thiagarajan (10 shared papers)Andreas Spanias (9 shared papers)Huan Song (1 shared paper)Pavan Turaga (1 shared paper)David Beymer (4 shared papers)Mahesh K. Banavar (5 shared papers)Suhas Ranganath (3 shared papers)Jannis Born (2 shared papers)
- Journals
- Cancer Research (2 papers)Patterns (2 papers)Scientific Reports (2 papers)International Journal of Artificial Intelligence Tools (1 paper)Computing in cardiology (1 paper)
- Partner nations
- United StatesSwitzerlandIsrael
In The Last Decade
Deepta Rajan
20 papers receiving 403 citations
Deepta Rajan's Hit Papers
Peers
Comparison fields: 5 of 87
- Health Informatics 32
- Health Information Management 60
- Signal Processing 97
- Artificial Intelligence 213
- Management Science and Operations Research 44
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
Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Attend and Diagnose: Clinical Time Series Analysis Using Attention Models Hit paper breakdown → | 2018 | 273 |
| 2 | 2021 | 39 | |
| 3 | 2022 | 24 | |
| 4 | 2013 | 13 | |
| 5 | 2020 | 11 | |
| 6 | 2014 | 11 | |
| 7 | 2021 | 11 | |
| 8 | 2018 | 8 | |
| 9 | 2014 | 6 | |
| 10 | 2013 | 3 | |
| 11 | 2012 | 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 | 2023 | 2 | |
| 16 | 2020 | 2 | |
| 17 | Can Deep Clinical Models Handle Real-World Domain Shifts? | 2018 | 1 |
| 18 | Interactive Signal Processing Education Applications for the Android Platform | 2019 | 1 |
| 19 | 2022 | 1 | |
| 20 | 2022 | 1 |
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 21 papers that have together received 417 indexed citations. Recurring topics across this work include Machine Learning in Healthcare (5 papers), COVID-19 diagnosis using AI (5 papers), Radiomics and Machine Learning in Medical Imaging (5 papers), ECG Monitoring and Analysis (3 papers), AI in cancer detection (3 papers), Medical Image Segmentation Techniques (2 papers), Sparse and Compressive Sensing Techniques (2 papers) and Experimental Learning in Engineering (2 papers). The work is most often cited by research in Health Informatics (32 citations), Health Information Management (60 citations), Signal Processing (97 citations), Artificial Intelligence (213 citations) and Management Science and Operations Research (44 citations). Deepta Rajan has collaborated with scholars based in United States, Switzerland and Israel. Frequent co-authors include Jayaraman J. Thiagarajan, Andreas Spanias, Huan Song, Pavan Turaga, David Beymer, Mahesh K. Banavar, Suhas Ranganath, Jannis Born, Matteo Manica and Photini Spanias. Their work appears in journals such as Cancer Research, Patterns, Scientific Reports, International Journal of Artificial Intelligence Tools and Computing in cardiology.
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.