Prostate-MRI reporting should be done with the aid of AI systems: Pros
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Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s00330-024-10909-y.pdf
Reference11 articles.
1. de Rooij M (2024) Prostate-MRI reporting should be done with the aid of AI systems: Cons. Eur Radiol. https://doi.org/10.1007/s00330-024-10898-y
2. Hamm CA, Baumgartner GL, Padhani AR et al (2024) Reduction of false positives using zone-specific prostate-specific antigen density for prostate MRI-based biopsy decision strategies. Eur Radiol. https://doi.org/10.1007/s00330-024-10700-z
3. Jorg T, Halfmann MC, Arnhold G et al (2023) Implementation of structured reporting in clinical routine: a review of 7 years of institutional experience. Insights Imaging 14:61. https://doi.org/10.1186/s13244-023-01408-7
4. Westphalen AC, McCulloch CE, Anaokar JM et al (2020) Variability of the positive predictive value of PI-RADS for prostate MRI across 26 centers: experience of the society of abdominal radiology prostate cancer disease-focused panel. Radiology 296:76–84. https://doi.org/10.1148/radiol.2020190646
5. Di Franco F, Souchon R, Crouzet S et al (2023) Characterization of high-grade prostate cancer at multiparametric MRI: assessment of PI-RADS version 2.1 and version 2 descriptors across 21 readers with varying experience (MULTI study). Insights Imaging 14:49. https://doi.org/10.1186/s13244-023-01391-z
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