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Testing an AI model that predicts when prostate cancer stops responding to hormone therapy

Tests an AI model predicting time to castration resistance in prostate cancer.

Plain-language title generated from the registry record
Registry title: Development and Prospective Validation of a Pathology-Based Artificial Intelligence Model for Predicting the Time to Castration Resistance of Prostate Cancer

Key facts

Where
Guangzhou, ChinaSee the site

Where in China

  • Sun Yat Sen Memorial Hospital of Sun Yat sen UniversityGuangzhou, ChinaNo longer taking part

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Trial details

Who runs it
Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
Trial code
NCT07376057
Record updated
29 January 2026
Original description
The goal of this predictive test is to prospectively test the performance of pre-developed artificial intelligence (AI) predictive model for predicting the time to castration resistance of prostate cancer. Investigators had developed this AI model based on deep learning algorithms in preliminary research, and it performed well in retrospective tests.Read full original descriptionShow less

Development and Prospective Validation of a Pathology-Based Artificial Intelligence Model for Predicting the Time to Castration Resistance of Prostate Cancer

The goal of this predictive test is to prospectively test the performance of pre-developed artificial intelligence (AI) predictive model for predicting the time to castration resistance of prostate cancer. Investigators had developed this AI model based on deep learning algorithms in preliminary research, and it performed well in retrospective tests.

Inclusion: Patients are diagnosed with intermediate- to high-risk prostate cancer; undergo prostate biopsy; Patients only received endocrine therapy for prostate cancer; Patients with complete clinical and pathological information; Patients agree to participate in this diagnostic test.

Exclusion: Patients with other tumors and undergo systemic therapy ; The patient refused to participate in this diagnostic test.

ClinicalTrials.gov NCT07376057