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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)....
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. |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2023
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Materias: | |
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 |
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