Your browser doesn't support javascript.
loading
Using ChatGPT to evaluate cancer myths and misconceptions: artificial intelligence and cancer information.
Johnson, Skyler B; King, Andy J; Warner, Echo L; Aneja, Sanjay; Kann, Benjamin H; Bylund, Carma L.
Afiliación
  • Johnson SB; Department of Radiation Oncology, University of Utah School of Medicine, Huntsman Cancer Institute, Salt Lake City, UT, USA.
  • King AJ; Cancer Control and Population Sciences, Huntsman Cancer Institute, Salt Lake City, UT, USA.
  • Warner EL; Cancer Control and Population Sciences, Huntsman Cancer Institute, Salt Lake City, UT, USA.
  • Aneja S; Department of Communication, University of Utah, Salt Lake City, UT, USA.
  • Kann BH; Cancer Control and Population Sciences, Huntsman Cancer Institute, Salt Lake City, UT, USA.
  • Bylund CL; College of Nursing, University of Utah, Salt Lake City, UT, USA.
JNCI Cancer Spectr ; 7(2)2023 03 01.
Article en En | MEDLINE | ID: mdl-36929393
ABSTRACT
Data about the quality of cancer information that chatbots and other artificial intelligence systems provide are limited. Here, we evaluate the accuracy of cancer information on ChatGPT compared with the National Cancer Institute's (NCI's) answers by using the questions on the "Common Cancer Myths and Misconceptions" web page. The NCI's answers and ChatGPT answers to each question were blinded, and then evaluated for accuracy (accurate yes vs no). Ratings were evaluated independently for each question, and then compared between the blinded NCI and ChatGPT answers. Additionally, word count and Flesch-Kincaid readability grade level for each individual response were evaluated. Following expert review, the percentage of overall agreement for accuracy was 100% for NCI answers and 96.9% for ChatGPT outputs for questions 1 through 13 (ĸ = ‒0.03, standard error = 0.08). There were few noticeable differences in the number of words or the readability of the answers from NCI or ChatGPT. Overall, the results suggest that ChatGPT provides accurate information about common cancer myths and misconceptions.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Asunto principal: Inteligencia Artificial / Neoplasias Tipo de estudio: Diagnostic_studies Límite: Humans País/Región como asunto: America do norte Idioma: En Revista: JNCI Cancer Spectr Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Asunto principal: Inteligencia Artificial / Neoplasias Tipo de estudio: Diagnostic_studies Límite: Humans País/Región como asunto: America do norte Idioma: En Revista: JNCI Cancer Spectr Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos