Shanu Sushmita
- Artificial Intelligence top 10%
- Information Systems top 10%
- Clinical Psychology
- Social Psychology
- Sociology and Political Science
- Co-authors
- Martine De CockSergio DavalosGolnoosh FarnadiMounia LalmasMarie‐Francine MoensFabio CelliDavid StillwellMichał Kosiński
- Topics
- Machine Learning in Healthcare (5 papers)Information Retrieval and Search Behavior (4 papers)Chronic Disease Management Strategies (3 papers)
- Journals
- User Modeling and User-Adapted InteractionACM SIGIR ForumNational Conference on Artificial Intelligence
- Partner nations
- United StatesUnited KingdomBelgium
In The Last Decade
Shanu Sushmita
13 papers receiving 290 citations
Peers
Comparison fields: 5 of 63
- Artificial Intelligence 120
- Information Systems 83
- Clinical Psychology 80
- Social Psychology 46
- Sociology and Political Science 43
Countries citing papers authored by Shanu Sushmita
This map shows the geographic impact of Shanu Sushmita'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 Shanu Sushmita with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shanu Sushmita more than expected).
Fields of papers citing papers by Shanu Sushmita
This network shows the impact of papers produced by Shanu Sushmita. 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 Shanu Sushmita. The network helps show where Shanu Sushmita may publish in the future.
Co-authorship network of co-authors of Shanu Sushmita
This figure shows the co-authorship network connecting the top 25 collaborators of Shanu Sushmita. A scholar is included among the top collaborators of Shanu Sushmita 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 Shanu Sushmita. Shanu Sushmita 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 | Predicting 30-Day Risk and Cost of "All-Cause" Hospital Readmissions | 14 |
| 3 | 2 | |
| 4 | 137 | |
| 5 | 6 | |
| 6 | 8 | |
| 7 | 36 | |
| 8 | 28 | |
| 9 | 4 | |
| 10 | 2 | |
| 11 | 51 | |
| 12 | Understanding domain "relevance" in web search | 5 |
| 13 | Using digest pages to increase user result space: Preliminary designs | 10 |
About Shanu Sushmita
Shanu Sushmita is a scholar working on Health Information Management, Artificial Intelligence and Signal Processing, having authored 13 papers that have together received 304 indexed citations. Recurring topics across this work include Machine Learning in Healthcare (5 papers), Information Retrieval and Search Behavior (4 papers) and Chronic Disease Management Strategies (3 papers). The work is most often cited by research in Health Information Management (24 citations), Clinical Psychology (80 citations) and Artificial Intelligence (120 citations). Shanu Sushmita has collaborated with scholars based in United States, United Kingdom and Belgium. Frequent co-authors include Martine De Cock, Sergio Davalos, Golnoosh Farnadi, Mounia Lalmas, Marie‐Francine Moens, Fabio Celli, David Stillwell, Michał Kosiński, Hideo Joho and Robert Villa. Their work appears in journals such as User Modeling and User-Adapted Interaction, ACM SIGIR Forum and National 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.