The primary mission of this pipeline is to deliver a seamless Machine Learning service, empowering users to take raw, unprocessed dataframes and effortlessly obtain predictions based on their specified target variable. Currently, this pipeline is tailored to handle dichotomous variables, offering a versatile tool for binary classification tasks, making it an invaluable asset for a wide range of applications.
The development of this Machine Learning pipeline emerged from a pressing need within the realm of oncology and precision medicine. Specifically, it was born out of the requirement to construct a predictive model for the efficacy of Immune Checkpoint Inhibitors (ICI) in the context of bladder cancer (BLCA) treatment.
Complete documentation can be found on this github. Trained models for BLCA response can be found in: https://github.com/EvolutionaryGenomics-GRIB/BLCA_ICI_Response_Predictor