Darsh Shah
Impact in
- Artificial Intelligence top 10%
- Topic Modeling
- Natural Language Processing Techniques
- Domain Adaptation and Few-Shot Learning
- Advanced Text Analysis Techniques
- Sentiment Analysis and Opinion Mining
- Text and Document Classification Technologies
-
- Multimodal Machine Learning Applications
Papers in
-
- Topic Modeling 8
- Natural Language Processing Techniques 4
- Advanced Text Analysis Techniques 2
- Machine Learning in Healthcare 1
- Speech and dialogue systems 1
-
- Meningioma and schwannoma management 2
- Co-authors
- Regina Barzilay (7 shared papers)Jiang Guo (1 shared paper)Tao Leí (4 shared papers)Luu Anh Tuan (1 shared paper)Tal Schuster (2 shared papers)Salvatore Romeo (1 shared paper)Alessandro Moschitti (1 shared paper)Preslav Nakov (1 shared paper)
- Journals
- World Neurosurgery (1 paper)JCO Precision Oncology (1 paper)Journal of Neuro-Oncology (1 paper)Healthcare (1 paper)Interdisciplinary Neurosurgery (1 paper)
- Partner nations
- United StatesIndiaQatar
In The Last Decade
Darsh Shah
15 papers receiving 266 citations
Peers
Comparison fields: 5 of 81
- Artificial Intelligence 193
- Computer Vision and Pattern Recognition 67
- Health Informatics 4
- Information Systems 30
- Family Practice 2
Countries citing papers authored by Darsh Shah
This map shows the geographic impact of Darsh Shah'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 Darsh Shah with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Darsh Shah more than expected).
Fields of papers citing papers by Darsh Shah
This network shows the impact of papers produced by Darsh Shah. 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 Darsh Shah. The network helps show where Darsh Shah may publish in the future.
Co-authors
The 25 scholars most cited alongside Darsh Shah, 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 | 2018 | 95 | |
| 2 | 2018 | 38 | |
| 3 | 2020 | 32 | |
| 4 | 2020 | 28 | |
| 5 | 2020 | 23 | |
| 6 | 2018 | 17 | |
| 7 | 2020 | 11 | |
| 8 | 2021 | 8 | |
| 9 | Are We Safe Yet? The Limitations of Distributional Features for Fake News Detection. | 2019 | 6 |
| 10 | 2021 | 5 | |
| 11 | 2022 | 5 | |
| 12 | 2023 | 3 | |
| 13 | 2022 | 3 | |
| 14 | 2021 | 2 | |
| 15 | 2020 | 1 | |
| 16 | 2025 | 0 |
About Darsh Shah
Darsh Shah is a scholar working on Artificial Intelligence, Epidemiology, Information Systems, Communication and Molecular Biology, having authored 16 papers that have together received 277 indexed citations. Recurring topics across this work include Topic Modeling (8 papers), Natural Language Processing Techniques (4 papers), Expert finding and Q&A systems (2 papers), Advanced Text Analysis Techniques (2 papers), Meningioma and schwannoma management (2 papers), Wikis in Education and Collaboration (1 paper), Machine Learning in Healthcare (1 paper) and Speech and dialogue systems (1 paper). The work is most often cited by research in Artificial Intelligence (193 citations), Computer Vision and Pattern Recognition (67 citations), Health Informatics (4 citations), Information Systems (30 citations) and Family Practice (2 citations). Darsh Shah has collaborated with scholars based in United States, India and Qatar. Frequent co-authors include Regina Barzilay, Jiang Guo, Tao Leí, Luu Anh Tuan, Tal Schuster, Salvatore Romeo, Alessandro Moschitti, Preslav Nakov, Manan Shah and Lili Yu. Their work appears in journals such as World Neurosurgery, JCO Precision Oncology, Journal of Neuro-Oncology, Healthcare and Interdisciplinary Neurosurgery.
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.