Secure Scalable Real-Time Machine Learning Platform for Healthcare

A machine learning system for healthcare applications comprises a data ingestion pipeline configured to automatically receive patient data including stored data from an EHR database and real-time data from a plurality of data sources, the data including, EHR records, claims data, and social determinants of health data; a data processing module configured to clean, extract, and process the received patient data; at least one predictive model configured to analyze the cleaned and processed data and determine a risk score for each patient; a configuration file defining the predictive model execution parameters; a tuning module configured to adjust parameters of the predictive model, including variables, thresholds, and coefficients; a retraining module configured to make further adjustments of the predictive model to remove inherent data biases; and a dashboard and reporting module configured to present the risk score to a patient care team.