Research Support - Development-to-Deployment Life Cycle
The development-to-deployment life cycle of the machine learning-based, center-specific (MLCS), prognostic model for use at point-of-care to support patient counseling
(A) The MLCS-based, PreIVF model (MLCS model) product life cycle comprises the steps of data pre-processing, model training and validation, deployment and post-deployment validation (or “live model validation”, LMV). MLCS1, MLCS2, etc. indicates that each MLCS model will be replaced by an updated MLCS model trained and tested with a more recent data set which may also become cumulatively larger. (B) Model pipeline supports feature testing, model training, validation analysis, deployment to production and quality testing.
Note: MLCS model = machine learning, center-specific model. In (B), “MLCS” is used generically to indicate the steps used for MLCS1, MLCS2 or any subsequent updates of MLCS model for a particular fertility center.