Abstract: A community vulnerability index dashboard includes a data ingestion logic module configured to automatically receive real-time and non-real-time data from a variety of sources including education agencies, law enforcement, health services agencies, healthcare agencies, medical insurance agencies, housing and transportation agencies, childcare licensing agencies, and non-emergency citywide services. The dashboard includes a data processing module that extracts and process the ingested data, and a data analysis logic module that analyzes the processed data to determine values for indicators and an overall vulnerability index value based on the values of the plurality of indicators to provide insight into the lives of residents living in a community on a block group level. The dashboard includes a data presentation dashboard interface to display an interactive choropleth map of the overall vulnerability index and indicator values on a block group level for the community of interest.

Abstract: 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.