Preethi Subramanian
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- Stock Market Forecasting Methods 2
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- Customer Service Quality and Loyalty 3
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- Radiomics and Machine Learning in Medical Imaging 2
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- Customer churn and segmentation 2
- Consumer Retail Behavior Studies 2
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- Digital Marketing and Social Media 2
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- Financial Distress and Bankruptcy Prediction 2
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- IgG4-Related and Inflammatory Diseases 1
- Co-authors
- Ramesh K. WaliHemant K. RoySamian SulaimanS.B. ChanEileen M. O’ReillyTrung Nghia VuStéphanie NougaretShivangi Vora
- Journals
- Journal of Clinical Oncology (1 paper)SHILAP Revista de lepidopterología (1 paper)Gastroenterology (1 paper)
- Partner nations
- MalaysiaUnited StatesIndia
In The Last Decade
Preethi Subramanian
14 papers receiving 60 citations
Peers
Comparison fields: 5 of 51
- Human-Computer Interaction 9
- Health Informatics 2
- Management Science and Operations Research 11
- Computer Vision and Pattern Recognition 12
- Information Systems 13
Countries citing papers authored by Preethi Subramanian
This map shows the geographic impact of Preethi Subramanian'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 Preethi Subramanian with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Preethi Subramanian more than expected).
Fields of papers citing papers by Preethi Subramanian
This network shows the impact of papers produced by Preethi Subramanian. 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 Preethi Subramanian. The network helps show where Preethi Subramanian may publish in the future.
Co-authorship network
The 23 scholars most cited alongside Preethi Subramanian, 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 | 2025 | 0 | |
| 2 | 2024 | 0 | |
| 3 | 2024 | 1 | |
| 4 | 2023 | 1 | |
| 5 | 2023 | 0 | |
| 6 | 2022 | 8 | |
| 7 | 2022 | 5 | |
| 8 | 2021 | 0 | |
| 9 | 2021 | 2 | |
| 10 | 2020 | 0 | |
| 11 | 2019 | 26 | |
| 12 | 2019 | 2 | |
| 13 | 2019 | 2 | |
| 14 | 2019 | 4 | |
| 15 | 2019 | 9 | |
| 16 | 2019 | 0 | |
| 17 | Artificial Intelligence Integration in Cloud-based Real-time Data Quality Assurance for Multi-Institutional Clinical Trials | 2018 | 1 |
| 18 | 2018 | 0 | |
| 19 | 2018 | 1 | |
| 20 | 2011 | 1 |
About Preethi Subramanian
Preethi Subramanian is a scholar working on Life-span and Life-course Studies, Marketing and Organizational Behavior and Human Resource Management, having authored 21 papers that have together received 65 indexed citations. Recurring topics across this work include Customer Service Quality and Loyalty (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers), Stock Market Forecasting Methods (2 papers), Customer churn and segmentation (2 papers), Digital Marketing and Social Media (2 papers), Consumer Retail Behavior Studies (2 papers), Financial Distress and Bankruptcy Prediction (2 papers) and IgG4-Related and Inflammatory Diseases (1 paper). The work is most often cited by research in Human-Computer Interaction (9 citations), Health Informatics (2 citations) and Management Science and Operations Research (11 citations). Preethi Subramanian has collaborated with scholars based in Malaysia, United States and India. Frequent co-authors include Ramesh K. Wali, Hemant K. Roy, Samian Sulaiman, S.B. Chan, Eileen M. O’Reilly, Trung Nghia Vu, Stéphanie Nougaret, Shivangi Vora, Qian Shi and Deborah Schrag. Their work appears in journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and Gastroenterology.
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.