A novel assessment of whole-mount Gleason grading in prostate cancer to identify candidates for radical prostatectomy: a machine learning-based multiomics study

Jing Ning, Clemens P. Spielvogel, David Haberl, Karolína Trachtová, Stefan Stoiber, Sazan Rasul, Vojtěch Bystrý, Gabriel Wasinger, Pascal Baltzer, Elisabeth Gurnhofer,

Theranostics · 2024 · 11 citations · 43 references

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Abstract

: The findings demonstrate a superior assessment of the developed multiomics-based ML model in whole-mount GG compared to the current clinical baseline of bxGG. This enables personalized patient management by identifying high-risk PCa patients for RP.

References

43