Vignette-based comparative analysis of ChatGPT and specialist treatment decisions for rheumatic patients: results of the Rheum2Guide study
Hannah Labinsky(Friedrich-Alexander-Universität Erlangen-Nürnberg), Johannes Knitza(Friedrich-Alexander-Universität Erlangen-Nürnberg), Sebastian Griewing(Philipps University of Marburg), Lea-Kristin Nagler(Universitätsklinikum Würzburg), Marc Schmalzing(Universitätsklinikum Würzburg), Peer Aries(Dermatologikum Hamburg), Michael Gernert(Universitätsklinikum Würzburg), Patrick‐Pascal Strunz(Universitätsklinikum Würzburg), Sebastian Kühn(Philipps University of Marburg), Anja Kroiß(Universitätsklinikum Würzburg), Martin Krusche(Universität Hamburg)
Cited by 13
Related Papers
Mobile Health Usage, Preferences, Barriers, and eHealth Literacy in Rheumatology: Patient Survey Study
|JMIR mhealth and uhealth|2020|215
2022 EULAR points to consider for remote care in rheumatic and musculoskeletal diseases
|Annals of the Rheumatic Diseases|2022|131
Accuracy, patient-perceived usability, and acceptance of two symptom checkers (Ada and Rheport) in rheumatology: interim results from a randomized controlled crossover trial
|Arthritis Research & Therapy|2021|73
Challenging ChatGPT 3.5 in Senology—An Assessment of Concordance with Breast Cancer Tumor Board Decision Making
|Journal of Personalized Medicine|2023|70