Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Evaluating Quality and Readability of AI-generated Information on Living Kidney Donation
6
Zitationen
3
Autoren
2024
Jahr
Abstract
Current LLM provides fairly accurate responses to common prospective living kidney donor questions; however, the generated information is complex and requires an advanced level of education. As LLMs become more relevant in the field of medical information, transplant providers should familiarize themselves with the shortcomings of these technologies.
Ähnliche Arbeiten
Comparison of Mortality in All Patients on Dialysis, Patients on Dialysis Awaiting Transplantation, and Recipients of a First Cadaveric Transplant
1999 · 5.266 Zit.
WORLD MEDICAL ASSOCIATION DECLARATION OF HELSINKI: Ethical Principles for Medical Research Involving Human Subjects
2001 · 3.534 Zit.
BIRTH AFTER THE REIMPLANTATION OF A HUMAN EMBRYO
1978 · 2.589 Zit.
Chronic Renal Failure after Transplantation of a Nonrenal Organ
2003 · 2.191 Zit.
Critical Care Medicine
1971 · 2.000 Zit.