Impact of COMORBIDities After Radical Cystectomy Using a Predictive Method With Artificial Intelligence

Clinician and the multidisciplinary team meeting in oncologic urology (MMO) play a key-role in the decision making. An unexplained surgeon attributable variance, probably linked to the subjective "eyeball test" effect, was identified as a strongest factor underlying non-compliance with guide line recommendations in the management of bladder cancer. So high-quality studies that identify barriers and modulators (such as comorbidities) of provider-level adoption of guidelines and how comorbidities are associated in making therapeutic choice and their impact in bladder cancer specific survival and overall survival, are crucial. To identify patients at high risk of early death, and to improve specific guideline for treatment might be decisive. In order to assess survival, where mortality events compete, it will be more appropriate to compute a Cumulative Incidence Function (namely CIF). The investigators will compare outcomes across patient populations to obtain information to improve clinical decision-making. Such learning will be done through the use of neural networks or by applying population-based approaches, such as Genetic Algorithms (GA), Ant Colony Systems (ACS) and Particle Swarm Optimization (PSO), using as a four-stage based approach. First, the investigators propose a "pretopology space" in order to study a dynamic phenomenon. Second, the investigators recall that the K-means approach remains one of the most used approaches for classifying a set of elements (patient…

This description comes directly from the study's public registry record.

Fabien SAINT, Pr  ·  03 22 45 59 52  ·  saint-fabien@chu-amiens.fr

Always discuss trial participation with your own doctor first.

Get one email when the public record changes — results posted, or the study's status changes. Nothing else, ever.

We email about this public record only. Unsubscribe anytime with one click. Never medical advice.