Can incorrect artificial intelligence (AI) results impact radiologists, and if so, what can we do about it? A multi-reader pilot study of lung cancer detection with chest radiography

OBJECTIVE: To examine whether incorrect AI results impact radiologist performance, and if so, whether human factors can be optimized to reduce error. METHODS: Multi-reader design, 6 radiologists interpreted 90 identical chest radiographs (follow-up CT needed: yes/no) on four occasions (09/20–01/22)....

Descripción completa

Detalles Bibliográficos
Autores principales: Bernstein, Michael H., Atalay, Michael K., Dibble, Elizabeth H., Maxwell, Aaron W. P., Karam, Adib R., Agarwal, Saurabh, Ward, Robert C., Healey, Terrance T., Baird, Grayson L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2023
Materias:
Chest
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10235827/
https://www.ncbi.nlm.nih.gov/pubmed/37266657
http://dx.doi.org/10.1007/s00330-023-09747-1

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10235827/
https://www.ncbi.nlm.nih.gov/pubmed/37266657
http://dx.doi.org/10.1007/s00330-023-09747-1

Ejemplares similares