This clinical trial focuses on testing the efficacy of different digital interventions to promote re-engagement in cancer-related long-term follow-up care for adolescent and young adult (AYA) survivors of childhood cancer.
This is a multi-center study and the aim is to develop and validate an Artificial Intelligence (AI) -based histologic analysis tool to predict responsiveness to intravesical Bacillus Calmette-Guérin (BCG) and intravesical chemotherapy in intermediate and high-risk non-muscle invasive bladder cancer patients.
Predicting Outcomes in Intermediate and High-risk Non-muscle Invasive Bladder Cancer Using Automated Analysis of Digital Pathology Data
Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.
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Sponsor: University of Texas Southwestern Medical Center
These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.