Metadata-Version: 2.1
Name: ehrzero
Version: 1.0.25
Summary: Zero-Knowledge Risk Oracle for predictive diagnoses of childhood neuropsychiatric disorders from sparse  electronic health records
Home-page: http://zed.uchicago.edu/
Author: Dymtro Onishchenko, Ishanu Chattopadhyay 
Author-email: ishanu@uchicago.edu
License: UNKNOWN
Description: ===============
        ehrzero
        ===============
        
        .. figure:: https://badge.fury.io/py/ehrzero.svg
           :alt: ehrzero PyPI Downloads
        
        .. image:: http://zed.uchicago.edu/logo/logozed1.png
           :height: 400px
           :scale: 50 %
           :alt: alternate text
           :align: center
        
        
        .. class:: no-web no-pdf
        
        :Info: Zero-Knowledge Risk Oracle
        :Author: ZeD@UChicago <zed.uchicago.edu>
        :Description: Estimation of the risk of future diagnoses of
        	      neuropsychiatric disorders (particularly autism) in early childhood,
        	      based on the diagnostic codes recorded during
        	      doctor visits. The prediction pipeline is based on
        	      inferring optimal stochastic generators for diagnostic code sequences,
        	      and detecting subtle deviations that drive up risk of
        	      an eventual neuropsychiatric diagnoses. The out-of-sample
        	      AUC score on the Truven dataset of insurance claims
        	      (close to 3 million children in out-of-sample data) is just over 80%,
        	      for both males and females.
        
        
        **Usage:**
        
        .. code-block::
        
            from ehrzero import ehrzero
            ehr.predict_with_confidence(SOURCE,n_first_weeks)
        
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/x-rst
