Predicting NMIBC Recurrence with AI

  • Research type

    Research Study

  • Full title

    Development and Implementation of a Personalized Machine Learning Model for the Accurate Prediction of Non-Muscle-Invasive Bladder Cancer (NMIBC) Recurrence

  • IRAS ID

    324876

  • Contact name

    Saram Abbas

  • Contact email

    s.abbas11@ncl.ac.uk

  • Sponsor organisation

    Newcastle University

  • Duration of Study in the UK

    3 years, 6 months, 1 days

  • Research summary

    Bladder cancer is a serious illness that often comes back after treatment. In this research project, we want to use advanced computer programs (especially Machine Learning techniques) to create a better way to predict when bladder cancer will return in people who have a certain type of the disease. By looking at a wide range of information about patients, our tool will be able to give each person a personalized prediction about their cancer. This will help doctors choose the best treatment and give patients a better chance of beating the disease. This new method has the potential to change how we treat this type of bladder cancer and improve outcomes for many patients.
    There are many ways that machine learning techniques can be used to improve the prediction of NMIBC recurrence. Historically, it has been challenging to study all this information at once, but with new computer based approaches much more can be processed simultaneously revealing important patterns in determining clinical outcomes that were previously missed. One approach is to use machine learning to analyse a large dataset of patient data, including demographic information, medical history, and other clinical features. By training a machine learning model on this data, this study will learn to identify patterns and relationships that are associated with a higher or lower risk of NMIBC recurrence. Then we can use this model to make personalized predictions for individual patients based on their unique characteristics and medical history. In a parallel approach we will use machine learning to identify specific biomarkers or other indicators that are predictive of NMIBC recurrence, which can then be used to develop more targeted treatment strategies.

  • REC name

    West of Scotland REC 5

  • REC reference

    23/WS/0169

  • Date of REC Opinion

    22 Nov 2023

  • REC opinion

    Favourable Opinion