Model development and deployment overview to create predictive models capable of creating real-time predictions. Process A transforms patient data into a format suitable for training and prediction tasks. Process B uses the output of process A to generate training samples that are then used to develop machine learning models. Process C uses the same output from process A to create samples derived from current hospital patients, enabling immediate predictions through the use of the trained models generated by process B. W&B, Weights & Biases.