Bright Huo

24 papers receiving 175 citations

Bright Huo's Hit Papers

Large Language Models for Chatbot Health Advice Studies 2025 · 59 citations
590Years since publication1020304050

Peers

Bright Huo
Comparison fields: 5 of 42
  • Health Informatics 33
  • Gastroenterology 18
  • Family Practice 3
  • Geriatrics and Gerontology 3
  • Applied Psychology 4
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Aymen Elfiky United States
Onofre Alarcón Spain
Jonah Zaretsky United States
Joseph Gabriel United Kingdom
Lisa Stump United States
Colette Dörr-Harim Germany
Lisa Patterson Canada
Yoav Brezinov Canada
Andrea Fares Bucci Italy
William Bender United States
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Citations per year

Countries citing papers authored by Bright Huo

Since Specialization
Citations

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

Fields of papers citing papers by Bright Huo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Bright Huo, 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 Bright Huo Line = papers co-authored together Bright Huo links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Large Language Models for Chatbot Health Advice Studies
Hit paper breakdown →
202559
2 202218
3 202214
4 202413
5 202311
6 202410
7 20167
8 20206
9 20245
10 20235
11 20185
12 20244
13 20224
14 20224
15 20233
16 20251
17 20251
18 20211
19 20251
20 20241

About Bright Huo

Bright Huo is a scholar working on Oncology, Surgery, Geriatrics and Gerontology, Health Informatics and Public Health, Environmental and Occupational Health, having authored 33 papers that have together received 177 indexed citations. Recurring topics across this work include Colorectal Cancer Surgical Treatments (4 papers), Artificial Intelligence in Healthcare and Education (4 papers), Diversity and Career in Medicine (3 papers), Frailty in Older Adults (3 papers), Innovations in Medical Education (3 papers), Colorectal Cancer Screening and Detection (2 papers), Gastroesophageal reflux and treatments (2 papers) and Grit, Self-Efficacy, and Motivation (2 papers). The work is most often cited by research in Health Informatics (33 citations), Gastroenterology (18 citations), Family Practice (3 citations), Geriatrics and Gerontology (3 citations) and Applied Psychology (4 citations). Bright Huo has collaborated with scholars based in Canada, United States and United Kingdom. Frequent co-authors include Stavros A. Antoniou, Yung Lee, Tyler McKechnie, Julio Mayol, Karim Ramji, Jeremy Steen, Arun James Thirunavukarasu, Wimonchat Tangamornsuksan, Stephanie Sanger and Dimitris Mavridis. Their work appears in journals such as Surgical Endoscopy, Journal of surgical education, Seminars in Thoracic and Cardiovascular Surgery, The Lancet Digital Health and Diseases of the Esophagus.

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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