Abstract: Systems and methods including one or more processors and one or more non-transitory computer readable media storing computing instructions that, when executed on the one or more processors, perform: receiving dispute resolution information from a user corresponding to a dispute, wherein the dispute resolution information comprises a first data input and a second data input; analyzing, with a first machine learning module in a first tier of a machine learning engine, the dispute resolution information from the user to identify a dispute reason; analyzing, with at least one of second and third machine learning modules in a second tier of the machine learning engine, the dispute resolution information based on the dispute reason, as identified; and determining a dispute resolution based on an output of the second tier of the machine learning engine to resolve the dispute. Other embodiments are disclosed herein.

Abstract: In various embodiments, network traffic data associated with an industrial network is monitored based on a networking event rule set related to defined networking events. The network traffic data is related to a set of asset devices in communication via the industrial network, and the networking event rule set is used to determine a networking event associated with the set of asset devices. A cybersecurity event level for the networking event is determined based on a comparison between a networking event feature set for the networking event and a predefined cybersecurity event feature set for a set of predefined cybersecurity events. In response to a determination that the cybersecurity event level for the networking event satisfies a predefined cybersecurity threat level threshold, a modification is made to one or more configuration parameters for one or more asset devices from the set of asset devices associated with the networking event.

Abstract: Systems and methods including one or more processors and one or more non-transitory computer readable media storing computing instructions that, when executed on the one or more processors, perform: receiving dispute resolution information from a user corresponding to a dispute, wherein the dispute resolution information comprises a first data input and a second data input; analyzing, with a first machine learning module in a first tier of a machine learning engine, the dispute resolution information from the user to identify a dispute reason; analyzing, with at least one of second and third machine learning modules in a second tier of the machine learning engine, the dispute resolution information based on the dispute reason, as identified; and determining a dispute resolution based on an output of the second tier of the machine learning engine to resolve the dispute. Other embodiments are disclosed herein.

Abstract: Certain examples provide systems and methods to assign clinical goals, care plans, and/or care pathways. An example system includes a rule engine including a particularly programmed processor to process ingested clinical data for a patient with respect to a goal, identify a rule applicable to the clinical data and goal for the patient, and apply the rule to the clinical data to generate at least one of an action or a suggestion for the patient based on applying the rule to the clinical data, the at least one of an action or a suggestion applicable to a care plan for the patient to achieve the goal. The example system also includes a rule repository storing rules and associated information for access by the rule engine.