Deep learning system for predicting outcomes in bladder cancer

Is this trial a fit for you?

A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.

What this trial studies

This research focuses on developing a deep learning-based system to predict overall and cancer-specific survival in patients with bladder cancer. By analyzing histopathological tissue slides and CT scans, the system aims to provide accurate prognostic stratification. The goal is to enhance treatment decision-making by offering insights into patient outcomes based on their unique cancer characteristics. The study will involve patients who have undergone surgical procedures for bladder cancer and have complete imaging and clinical data.

Why it matters

Who can join: the full rules

Inclusion Criteria:

* patients with bladder cancer who had surgery like radical cystectomy or transurethral resection of bladder tumour (TURBT)
* contrast-CT scan less than two weeks before surgery
* complete CT image data and clinical data
* complete whole slide image data

Exclusion Criteria:

* patients with a postoperative diagnosis of non-urothelial carcinoma
* poor quality of CT images

Where it's running

• Department of Urology, The First Affiliated Hospital of Chongqing Medical University
  Chongqing, Chongqing Municipality, China Recruiting

Study contacts

• Study coordinator: QuanHao He
• Email: 2020120460@stu.cqmu.edu.cn
• Phone: 800-555-5555

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How to take part

1. Review the eligibility criteria above with your treating physician.
2. Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
3. Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.