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Author

R. Etzioni

2 papers indexed here

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Jul 2026

TrajSurv-mPC: Learning From Prostate-Specific Antigen Trajectories for Interpretable and Generalizable Survival Prediction in Metastatic Prostate Cancer.

PURPOSE Conventional prognostic models for metastatic prostate cancer (mPC) typically rely on summary features like prostate-specific antigen (PSA) doubling time, often obscuring informative longitudinal dynamics. We developed TrajSurv-mPC, a flexible deep learning framework that analyzes full premetastasis patient tra...

Si-Hang Zeng, Lukas Owens, Lucas J. Liu et al. · 0 citations
Open access Aug 2026

Deep learning-based histologic classifiers enable molecular subtyping of metastatic prostate cancer.

Metastatic prostate cancer is a clinically and molecularly heterogeneous disease. Under the selective pressure of androgen receptor (AR)-directed therapies, resistant phenotypes frequently emerge, posing significant diagnostic and therapeutic challenges. Neuroendocrine prostate cancer (NEPC) is a clinically important p...

Zhi-Jun Chen, Erolcan Sayar, D. Guevara et al. · 0 citations

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