Robert Chew

1.9k citations
39 papers · 514 · 1 hit paper · h-index 12

Impact in

Papers in

Robert Chew

37 papers receiving 500 citations

Robert Chew's Hit Papers

Data extraction for evidence synthesis using a large language model: A proof‐of‐concept study 2024 · 70 citations
700+1Years since publication204060

Peers

Robert Chew
Comparison fields: 5 of 111
  • Health Informatics 28
  • Statistics, Probability and Uncertainty 23
  • Media Technology 22
  • Health 17
  • Artificial Intelligence 72
Replace Adyasha Maharana with:
Adyasha Maharana United States
Charles T. Gray Australia
Rémi Rampin United States
Shaw‐Hwa Lo United States
Camila P. E. de Souza Canada
Qingqing Chen United States
Florian Pfisterer Germany
Dexuan Sha United States
Gayathri Devi Nadarajan Singapore
Blessing Ogbuokiri South Africa
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Citations per field
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Citations per year

Countries citing papers authored by Robert Chew

Since Specialization
Citations

This map shows the geographic impact of Robert Chew'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 Robert Chew with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Robert Chew more than expected).

Fields of papers citing papers by Robert Chew

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Robert Chew. 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 Robert Chew. The network helps show where Robert Chew may publish in the future.

Co-authors

The 25 scholars most cited alongside Robert Chew, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Robert Chew Line = papers co-authored together Robert Chew links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 39 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202079
2
Data extraction for evidence synthesis using a large language model: A proof‐of‐concept study
Hit paper breakdown →
202470
3 201858
4 201758
5 202434
6 201730
7 201823
8 201923
9 202420
10 201920
11 202111
12 201911
13 20188
14 20218
15 20178
16 20228
17 20246
18 20254
19 20224
20 20253

About Robert Chew

Robert Chew is a scholar working on Artificial Intelligence, Statistics, Probability and Uncertainty, Communication, Molecular Biology and Health, having authored 39 papers that have together received 514 indexed citations. Recurring topics across this work include Meta-analysis and systematic reviews (3 papers), Adversarial Robustness in Machine Learning (2 papers), Hate Speech and Cyberbullying Detection (2 papers), Microbial infections and disease research (2 papers), Topic Modeling (2 papers), Machine Learning and Data Classification (2 papers), Biomedical Text Mining and Ontologies (2 papers) and Complex Network Analysis Techniques (2 papers). The work is most often cited by research in Health Informatics (28 citations), Statistics, Probability and Uncertainty (23 citations), Media Technology (22 citations), Health (17 citations) and Artificial Intelligence (72 citations). Robert Chew has collaborated with scholars based in United States, Austria and Germany. Frequent co-authors include Annice Kim, Antonio A. Morgan‐López, Rainer Hilscher, Leila C. Kahwati, Shannon Kugley, Karen Crotty, Gerald Gartlehner, Meera Viswanathan, Ian B. Thomas and D. Temple. Their work appears in journals such as JMIR Public Health and Surveillance, Journal of Medical Internet Research, Research Synthesis Methods, PLoS Medicine and Bioinformatics.

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.

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