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Editorial
. 2024 May 24:14:1421542.
doi: 10.3389/fonc.2024.1421542. eCollection 2024.

Editorial: PET/CT and MRI in prostate cancer

Fabio Grizzi  1   2 , Gianluigi Taverna  3
Affiliations
Editorial

Editorial: PET/CT and MRI in prostate cancer

Fabio Grizzi et al. Front Oncol. .
No abstract available

Keywords: MRI; PET/CT; artificial intelligence; diagnosis; prostate cancer.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.

Figures

Figure 1
Figure 1
The diagnostic pathway for PCa strives to achieve timely identification of clinically significant PCa while minimizing the detection of insignificant cases. This approach seeks to strike a balance between diagnostic accuracy and the potential burden on individuals and healthcare providers. Utilizing artificial intelligence, we integrate data from various scales (A) to enhance the diagnosis and treatment of prostate cancer. Within the collected dataset, the AI-driven system identifies and extrapolates the features and data points most pertinent to generating the ultimate outcome (B). The integration of diverse data and features culminates in a refined categorization of the condition (C), emphasizing that integration involves intricate connections among diverse characteristics observed across multiple scales, rather than a mere summation of individual outcomes.
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