ASSESSING THE QUALITY OF ARTIFICIAL INTELLIGENCE RESPONSES AND RESISTANCE TO SYCOPHANCY IN PROVIDING PATIENT-CENTERED MEDICAL ADVICE ON GASTROESOPHAGEAL REFLUX DISEASE

Clin Gastroenterol Hepatol. 2024 Dec 15:S1542-3565(24)01087-5. doi: 10.1016/j.cgh.2024.10.033. Online ahead of print.

Authors

Benjamin Douglas Liu¹, Steve D'Souza², Melina Roy³, MetroHealth Dietitians⁴, Sherif Saleh², Ronnie Fass², Gengqing Song⁵

Affiliations

¹ Department of Medicine.
² Division of Gastroenterology and Hepatology.
³ Department of Nutrition Services, MetroHealth Medical Center, Case Western Reserve University, Cleveland, Ohio.
⁴ Department of Obstetrics and Gynecology, MetroHealth Medical Center.
⁵ Division of Gastroenterology and Hepatology,. Electronic address: [email protected].

PMID: 39689775
DOI: 10.1016/j.cgh.2024.10.033

No abstract available

Keywords: AI Sycophancy; Artificial Intelligence; GERD; Patient Education.