Predicting efficacy of preventative measures to mitigate spread of a pathogen and illnesses caused therefrom using machine learning models
AssigneeGeneral Genomics, Inc.
InventorsWarren Dennis GIECK, Aronjol David ROSENTHAL
Life of this patent
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Abstract
Embodiments of the present disclosure generally relate to methods for analyzing the effectiveness of preventative measures on the spread of illnesses, such as COVID-19, on living organisms. More particularly, embodiments of the present disclosure relate to methods for identifying the effectiveness of preventative measures, processes, equipment and other available data, and providing indicators and methods of visualization the effectiveness of preventative measures on the spread of an illness.
Claims40
A method for predicting efficacy of preventative measures to mitigate spread of a pathogen and illnesses caused therefrom, comprising:
- receiving a data set including a plurality of records, each respective record including at least information identifying a preventative measure and an efficacy of the preventative measure;
- training one or more machine learning models to predict an efficacy of a preventative measure based on the received data set;
- and
- deploying the trained one or more machine learning models to a computing system for use in recommending one or more preventative measures to implement in response to a pathogen.
A method for recommending preventative measures to implement to mitigate spread of a pathogen and illnesses caused therefrom, comprising:
- receiving a request for recommended preventative measures to implement, the request including at least an identification of the pathogen;
- identifying the recommended preventative measures based on at least the identification of the pathogen and one or more trained machine learning models;
- and
- outputting information about the identified preventative measures.
A system for recommending preventative measures to implement to mitigate spread of a pathogen and illnesses caused therefrom, comprising:
- a memory having instructions stored thereon;
- and
- a processor configured to execute the instructions to cause the system to:
- receive a request for recommended preventative measures to implement, the request including at least an identification of the pathogen;
- identify the recommended preventative measures based on at least the identification of the pathogen and one or more trained machine learning models;
- and
- output information about the identified preventative measures.
A method for predicting efficacy of preventative measures to mitigate spread of a pathogen and illnesses caused therefrom, comprising:
- receiving a data set including a plurality of records, each respective record including at least information identifying a preventative measure, an efficacy of the preventative measure, a pathogen against which the preventative measure is targeted, and information about a built environment in which the preventative measure is installed;
- training one or more machine learning models to predict an efficacy of a preventative measure based on the received data set;
- and
- deploying the trained one or more machine learning models to a computing system for use in recommending one or more preventative measures to implement in response to a pathogen.
A method for recommending preventative measures to implement to mitigate spread of a pathogen and illnesses caused therefrom, comprising:
- receiving a request for recommended preventative measures to implement, the request including at least an identification of the pathogen and information about a built environment in which a preventative measure is to be implemented;
- identifying the recommended preventative measures based on at least the identification of the pathogen and one or more trained machine learning models;
- and
- outputting information about the identified preventative measures.
A system for recommending preventative measures to implement to mitigate spread of a pathogen and illnesses caused therefrom, comprising:
- a memory having instructions stored thereon;
- and
- a processor configured to execute the instructions to cause the system to:
- receive a request for recommended preventative measures to implement, the request including at least an identification of the pathogen;
- identify the recommended preventative measures based on at least the identification of the pathogen and one or more trained machine learning models;
- and
- output information about the identified preventative measures.
Dependencies are inferred from the claim text.