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/Data Driven Featurization And Modeling
Abstract

Computer-implemented systems and methods are disclosed for automatically generating predictive models using data driven featurization. The systems and methods provide for obtaining data associated with a target event, annotating the data to identify a target event and establishing one or more limits on the data, censoring the data based on the annotations, determining features of the censored data, and analyzing the features to determine a predictive model. In some embodiments, the systems and methods further provide for converting the features into a binary representation and analyzing the binary representation to produce the predictive model.

Full Text

What is claimed is:

Computer-implemented systems and methods are disclosed for automatically generating predictive models using data driven featurization. The systems and methods provide for obtaining data associated with a target event, annotating the data to identify a target event and establishing one or more limits on the data, censoring the data based on the annotations, determining features of the censored data, and analyzing the features to determine a predictive model. In some embodiments, the systems and methods further provide for converting the features into a binary representation and analyzing the binary representation to produce the predictive model.
Timeline
Filed
02/20/2026
Published
06/25/2026
Granted
Not Available
IPC Codes(5)
G16H 10/40:for data related to laboratory analysis, e.g. patient specimen analysis
G06N 5/04:Inference or reasoning models
G06N 20/00:Machine learning