Automated survey collection with LLM-based conversational agents
Our study highlights the potential of LLM agents in conducting and analyzing phone surveys for healthcare applications. By reducing the workload on human interviewers and offering a scalable solution, this approach paves the way for real-world, end-to-end AI-powered phone survey collection systems.
Authors
- Nicholas J Dobbins (ORCID: https://orcid.org/0000-0002-3598-8747)
- Sean D. Mooney (ORCID: https://orcid.org/0000-0003-2654-0833)
- Kurmanbek Kaiyrbekov (ORCID: https://orcid.org/0000-0001-7635-1243)
Institutions
- Johns Hopkins University (US)
- Johns Hopkins Medicine (US)
- National Human Genome Research Institute (US)
Publication Details
- Journal
- JAMIA Open
- Published
- 2025-09-02
- DOI
- https://doi.org/10.1093/jamiaopen/ooaf103
- Citations
- 1
- Primary Topic
- Semantic Web and Ontologies
- Type
- article
- Field-Weighted Citation Impact
- 2.48
Funders
- National Institutes of Health