Karan Singhal
Impact in
- Health Informatics top 0.05%
- Artificial Intelligence in Healthcare and Education
- Artificial Intelligence top 2%
- Topic Modeling
- Machine Learning in Healthcare
- AI in cancer detection
Papers in
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- Career Development and Diversity 1
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- Artificial Intelligence in Healthcare and Education 1
- Co-authors
- Upasak Das (3 shared papers)Eva M. Sierminska (1 shared paper)Balder ten Cate (1 shared paper)Karthik Raman (1 shared paper)Ankur Sarin (2 shared papers)Joshua V. Dillon (1 shared paper)Elahe Vedadi (1 shared paper)Warren R. Morningstar (1 shared paper)
- Journals
- Feminist Economics (1 paper)International Journal of Educational Development (1 paper)International Journal of Inclusive Education (1 paper)Nature (1 paper)Canadian Journal of Development Studies/Revue canadienne d études du développement (1 paper)
- Partner nations
- United StatesIndiaLuxembourg
In The Last Decade
Karan Singhal
8 papers receiving 2.1k citations
Karan Singhal's Hit Papers
Peers
Comparison fields: 5 of 135
- Health Informatics 1.4k
- Artificial Intelligence 614
- Health Information Management 84
- Computer Vision and Pattern Recognition 141
- Statistics, Probability and Uncertainty 31
Countries citing papers authored by Karan Singhal
This map shows the geographic impact of Karan Singhal'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 Karan Singhal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Karan Singhal more than expected).
Fields of papers citing papers by Karan Singhal
This network shows the impact of papers produced by Karan Singhal. 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 Karan Singhal. The network helps show where Karan Singhal may publish in the future.
Co-authors
The 8 scholars most cited alongside Karan Singhal, 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 | Large language models encode clinical knowledge Hit paper breakdown → | 2023 | 2166 |
| 2 | 2017 | 11 | |
| 3 | 2022 | 7 | |
| 4 | 2019 | 6 | |
| 5 | 2023 | 6 | |
| 6 | 2023 | 2 | |
| 7 | 2024 | 2 | |
| 8 | 2022 | 1 | |
| 9 | 2024 | 1 |
About Karan Singhal
Karan Singhal is a scholar working on Safety Research, Health Informatics, Education, Gender Studies and Artificial Intelligence, having authored 9 papers that have together received 2.2k indexed citations. Recurring topics across this work include School Choice and Performance (3 papers), Artificial Intelligence in Healthcare and Education (1 paper), Privacy-Preserving Technologies in Data (1 paper), Career Development and Diversity (1 paper), Gender Diversity and Inequality (1 paper), Topic Modeling (1 paper), Mathematics Education and Pedagogy (1 paper) and Education, Achievement, and Giftedness (1 paper). The work is most often cited by research in Health Informatics (1.4k citations), Artificial Intelligence (614 citations), Health Information Management (84 citations), Computer Vision and Pattern Recognition (141 citations) and Statistics, Probability and Uncertainty (31 citations). Karan Singhal has collaborated with scholars based in United States, India and Luxembourg. Frequent co-authors include Upasak Das, Eva M. Sierminska, Balder ten Cate, Karthik Raman, Ankur Sarin, Joshua V. Dillon, Elahe Vedadi and Warren R. Morningstar. Their work appears in journals such as Feminist Economics, International Journal of Educational Development, International Journal of Inclusive Education, Nature and Canadian Journal of Development Studies/Revue canadienne d études du développement.
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.