The effect of using a large language model to respond to patient messages
Brigham and Women's Hospital · Dana-Farber Brigham Cancer Center · +8 more institutions
Indexed incrossrefdoajpubmed
Abstract
No abstract available for this paper.
Citation impact
118
total citations
- FWCI
- 12.49
- Percentile
- 100%
- References
- 9
Citations per year
Authors
17- SCShan ChenCorresponding
Brigham and Women's Hospital
- MGMarco Guevara-Vega
Brigham and Women's Hospital, Dana-Farber Brigham Cancer Center
- SMShalini Moningi
Brigham and Women's Hospital, Dana-Farber Cancer Institute, Dana-Farber Brigham Cancer Center
- FHFrank Hoebers
Dana-Farber Brigham Cancer Center
- HEHesham Elhalawani
Brigham and Women's Hospital, Dana-Farber Cancer Institute, Dana-Farber Brigham Cancer Center
Topics & keywords
Topics
Keywords
- Computer science
- Psychology
- Natural language processing
No related works found for this paper.
Funding
- AAAmerican Association for Cancer Research
- BSBristol-Myers Squibb
- PPfizer
- AAstraZenecaAward: U01CA209414
- GSGilead Sciences
- VMVarian Medical Systems
- VViewRay
- NINational Institutes of HealthAwards: K08DE030216, U01CA209414, R01LM012973, R01MH126977, U24CA194354, OT2OD032701, R35CA22052, R01GM114355, U01CA190234, K08DE030216-01, R01EB017205, U54CA274516
- NINational Institute on Drug AbuseAwards: R01LM012973, R01DA051464
- HEH2020 European Research Council
- NINational Institutes of Health, Pakistan