Priyanka Gupta
Impact in
- Health Information Management top 10%
- Artificial Intelligence in Healthcare
- Information Systems top 5%
- Recommender Systems and Techniques
Papers in
-
- Topic Modeling 4
- Machine Learning in Healthcare 2
- Advanced Graph Neural Networks 2
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- Recommender Systems and Techniques 4
- Co-authors
- Lovekesh Vig (8 shared papers)Gautam Shroff (8 shared papers)D. Garg (2 shared papers)Pankaj Malhotra (3 shared papers)Vishnu Tv (2 shared papers)Puneet Agarwal (1 shared paper)Arup Roy (1 shared paper)
- Journals
- PubMed (1 paper)Annual Conference of the PHM Society (2 papers)International Journal Of Engineering And Computer Science (1 paper)Cureus (1 paper)International Joint Conference on Artificial Intelligence (1 paper)
- Partner nations
- India
In The Last Decade
Priyanka Gupta
9 papers receiving 213 citations
Peers
Comparison fields: 5 of 61
- Health Information Management 23
- Information Systems 117
- Artificial Intelligence 139
- Management Science and Operations Research 36
- Medical Laboratory Technology 3
Countries citing papers authored by Priyanka Gupta
This map shows the geographic impact of Priyanka Gupta'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 Priyanka Gupta with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Priyanka Gupta more than expected).
Fields of papers citing papers by Priyanka Gupta
This network shows the impact of papers produced by Priyanka Gupta. 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 Priyanka Gupta. The network helps show where Priyanka Gupta may publish in the future.
Co-authors
The 7 scholars most cited alongside Priyanka Gupta, 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 | 2019 | 80 | |
| 2 | 2019 | 53 | |
| 3 | 2021 | 22 | |
| 4 | NISER: Normalized Item and Session Representations with Graph Neural Networks | 2019 | 20 |
| 5 | 2018 | 14 | |
| 6 | Using Features From Pre-trained TimeNET For Clinical Predictions. | 2018 | 14 |
| 7 | 2018 | 11 | |
| 8 | 2018 | 6 | |
| 9 | 2024 | 2 | |
| 10 | 2024 | 0 |
About Priyanka Gupta
Priyanka Gupta is a scholar working on Artificial Intelligence, Information Systems, Signal Processing, Health Information Management and Control and Systems Engineering, having authored 10 papers that have together received 222 indexed citations. Recurring topics across this work include Recommender Systems and Techniques (4 papers), Topic Modeling (4 papers), Time Series Analysis and Forecasting (3 papers), Artificial Intelligence in Healthcare (2 papers), Machine Learning in Healthcare (2 papers), Advanced Graph Neural Networks (2 papers), Fault Detection and Control Systems (2 papers) and Advanced Bandit Algorithms Research (2 papers). The work is most often cited by research in Health Information Management (23 citations), Information Systems (117 citations), Artificial Intelligence (139 citations), Management Science and Operations Research (36 citations) and Medical Laboratory Technology (3 citations). Priyanka Gupta has collaborated with scholars based in India. Frequent co-authors include Lovekesh Vig, Gautam Shroff, D. Garg, Pankaj Malhotra, Vishnu Tv, Puneet Agarwal and Arup Roy. Their work appears in journals such as PubMed, Annual Conference of the PHM Society, International Journal Of Engineering And Computer Science, Cureus and International Joint 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.