US 2020/0051696 A1 · METHOD FOR TRANSFORMING PATIENT DATA INTO IMAGES FOR INFECTION PREDICTION

Abstract

A method of determining the infection risk probability for a patient, including: encoding physiological data of the patient into a first synthetic image; encoding environmental data of the patient into a second synthetic image; determining an intrinsic probability of infection for the patient based upon the first synthetic image and the second synthetic image using a machine learning model; generating a graphical model based upon the patient and other patients based upon similarity scores between the patient and the other patients; and determining the infection risk probability for the patient based upon the graphical model and the intrinsic probability of infection for the patient and the other patients.

Claims24

Dependent claims

A method of determining the infection risk probability for a patient, comprising:

encoding physiological data of the patient into a first synthetic image;
encoding environmental data of the patient into a second synthetic image;
determining an intrinsic probability of infection for the patient based upon the first synthetic image and the second synthetic image using a machine learning model;
determining patterns of infection transmission by generating a graphical model based upon the intrinsic probability of patients based upon similarity scores between the patient and the other patients;
and
determining the infection risk probability for the patient based upon the graphical model and the intrinsic probability of infection for the patient and the other patients.

3 more elements

A non-transitory machine-readable storage medium encoded with instructions for deterring

the infection risk probability for a patient, comprising:
instructions for encoding physiological data of the patient into a first synthetic image;
instructions for encoding environmental data of the patient into a second synthetic image;
instructions for determining an intrinsic probability of infection for the patient based upon the first synthetic image and the second synthetic image using a machine learning model;
instructions for generating a graphical model based upon the patient and other patients based upon similarity scores between the patient and the other patients;
and
instructions for determining the infection risk probability for the patient based upon the graphical model and the intrinsic probability of infection for the patient and the other patients.

4 more elements

Dependencies are inferred from the claim text.

Method for transforming patient data into images for infection prediction

Life of this patent

Method for transforming patient data into images for infection prediction

Life of this patent

Abstract

Claims24