Abstract: Methods and systems for a cough detection system are provided. The methods and systems include operations comprising: receiving an utterance comprising a cough from a user; determining one or more environmental factors, one or more health related factors, or both associated with the user; processing the utterance with a machine learning technique to generate an illness prediction, the machine learning technique being trained to establish a relationship between a plurality of training cough utterances and a plurality of illnesses corresponding to the plurality of training cough utterances; applying a weight to the illness prediction based on the one or more environmental factors, health related factors, or both associated with the user; and triggering an alert representing the illness prediction based on the weighted illness prediction.

Abstract: A package delivery system for delivering a plurality of packages with one or more unmanned aerial vehicles (UAVs) includes a package receptacle to receive and store the plurality of packages. A charging station charges a plurality of UAV batteries which power the one or more UAVs. A UAV landing pad permits the one or more UAVs to land thereon. A loader loads a package of the plurality of packages and/or a UAV battery of the plurality of UAV batteries onto the UAVs when the UAVs are on the UAV landing pad. A transporter moves the packages and/or the UAV batteries s toward the loader.

Abstract: A quality assurance system includes a mainframe deployment device in communication with a mainframe device with a codebase. The mainframe deployment device initializes a branch repository corresponding to a code region of the codebase, identifies, for a code element of the code region, a timestamp indicating a creation time and a user identifier indicating an owner, populates the branch repository with the code element based on the code region and the timestamp, applies a code security scan to the branch repository to identify and resolve a code security issue, and applies a code quality scan to the branch repository to identify a code quality issue in the code element, assign the code element to the user identifier based at least partially on the timestamp, and route the code element along with information regarding the code quality issue to correct the code quality issue in the code element.

Abstract: A system and method for controlling an autonomous unmanned aerial vehicle for retrieval and delivery of a medical package includes determining a thermal control period for the medical package. The disclosure also includes identifying a relevant retrieval location corresponding to the medical package. The disclosure also includes identifying at least one environmental characteristic of an environment that includes a delivery three-dimensional flight path between the relevant retrieval location and a delivery location, wherein the at least one environmental characteristic indicates an actual weather value at the relevant retrieval location. The disclosure also includes determining whether to retrieve the medical package based on the thermal control period and the at least one environmental characteristic, using the unmanned aerial vehicle.

Abstract: A package delivery system for delivering a plurality of packages with one or more unmanned aerial vehicles (UAVs) includes a package receptacle to receive and store the plurality of packages. A charging station charges a plurality of UAV batteries which power the one or more UAVs. A UAV landing pad permits the one or more UAVs to land thereon. A loader loads a package of the plurality of packages and/or a UAV battery of the plurality of UAV batteries onto the UAVs when the UAVs are on the UAV landing pad. A transporter moves the packages and/or the UAV batteries s toward the loader.

Abstract: A system and method for controlling an autonomous unmanned aerial vehicle for retrieval and delivery of a medical package includes determining a thermal control period for the medical package. The disclosure also includes identifying a relevant retrieval location corresponding to the medical package. The disclosure also includes identifying at least one environmental characteristic of an environment that includes a delivery three-dimensional flight path between the relevant retrieval location and a delivery location, wherein the at least one environmental characteristic indicates an actual weather value at the relevant retrieval location. The disclosure also includes determining whether to retrieve the medical package based on the thermal control period and the at least one environmental characteristic, using the unmanned aerial vehicle.

Abstract: A quality assurance system includes a mainframe deployment device in communication with a mainframe device with a codebase. The mainframe deployment device initializes a branch repository corresponding to a code region of the codebase, identifies, for a code element of the code region, a timestamp indicating a creation time and a user identifier indicating an owner, populates the branch repository with the code element based on the code region and the timestamp, applies a code security scan to the branch repository to identify and resolve a code security issue, and applies a code quality scan to the branch repository to identify a code quality issue in the code element, assign the code element to the user identifier based at least partially on the timestamp, and route the code element along with information regarding the code quality issue to correct the code quality issue in the code element.

Abstract: A package delivery system for delivering a plurality of packages with one or more unmanned aerial vehicles (UAVs) includes a package receptacle to receive and store the plurality of packages. A charging station charges a plurality of UAV batteries which power the one or more UAVs. A UAV landing pad permits the one or more UAVs to land thereon. A loader loads a package of the plurality of packages and/or a UAV battery of the plurality of UAV batteries onto the UAVs when the UAVs are on the UAV landing pad. A transporter moves the packages and/or the UAV batteries s toward the loader.

Abstract: A system and method for controlling an autonomous unmanned aerial vehicle for retrieval and delivery of a medical package includes determining a thermal control period for the medical package. The disclosure also includes identifying a relevant retrieval location corresponding to the medical package. The disclosure also includes identifying at least one environmental characteristic of an environment that includes a delivery three-dimensional flight path between the relevant retrieval location and a delivery location, wherein the at least one environmental characteristic indicates an actual weather value at the relevant retrieval location. The disclosure also includes determining whether to retrieve the medical package based on the thermal control period and the at least one environmental characteristic, using the unmanned aerial vehicle.

Abstract: A method for providing mainframe codebase maintenance and security is performed by a mainframe deployment device. The method includes importing the mainframe codebase from a mainframe device. The mainframe codebase includes at least one code region including at least one code element. The method also includes identifying the code regions and initializing a branch repository corresponding to at least one identified code region. The method includes querying the imported mainframe codebase to identify, for the code elements, a user identifier and a source region. The method includes populating the branch repositories with the code elements based on the respective source region. The method includes applying a code quality scan to the populated branch repositories to identify a code quality issue in the respective code elements. The method also includes submitting at least one code element having an identified code quality issue to a user device correct the code quality issues.

Abstract: A computer system includes memory hardware and processor hardware configured to execute stored instructions. The instructions include training a machine learning model with the historical feature vector inputs including multiple audio data entries and multiple claims data entries, to generate a condition likelihood output indicative of a specified condition associated with one of multiple historical database entities. The instructions include for each of a set of multiple database entities, generating a feature vector input according to audio data and the claims data associated with the entity, processing the feature vector input with the machine learning model to generate the condition likelihood output, and assigning the database entity to an identified condition subset in response to determining that the condition likelihood output is greater than a specified likelihood threshold.

Abstract: A machine learning process for use with a pharmacy benefits management system. The machine learning process identifies a first predicted set of drug benefit claims impacted by a pricing error, reprices a sample of the first predicted set of drug benefit claims to adjust for the error, and trains a predictive model as a function of the repriced sample. Based on the trained model, the machine learning process predicts a second predicted set of drug benefit claims impacted by the error and initiates automatic repricing.

Abstract: A machine learning process for use with a pharmacy benefits management system. The machine learning process identifies a first predicted set of drug benefit claims impacted by a pricing error, reprices a sample of the first predicted set of drug benefit claims to adjust for the error, and trains a predictive model as a function of the repriced sample. Based on the trained model, the machine learning process predicts a second predicted set of drug benefit claims impacted by the error and initiates automatic repricing.

Abstract: Methods and systems for a cough detection system are provided. The methods and systems include operations comprising: receiving an utterance comprising a cough from a user; determining one or more environmental factors, one or more health related factors, or both associated with the user; processing the utterance with a machine learning technique to generate an illness prediction, the machine learning technique being trained to establish a relationship between a plurality of training cough utterances and a plurality of illnesses corresponding to the plurality of training cough utterances; applying a weight to the illness prediction based on the one or more environmental factors, health related factors, or both associated with the user; and triggering an alert representing the illness prediction based on the weighted illness prediction.

Abstract: A mainframe deployment device for deploying code to a mainframe device in a stable, self-correcting manner is described. The mainframe deployment device is configured to receive a code section from the software management device, identify a set of valid sub-components from the code section using a dispatcher service associated with the dispatcher device, identify a set of elements in the code section identified for deployment, request the at least one testing service to perform at least one set of code diagnostics to determine whether the code section satisfies build requirements, attempt to create a deployment package from the code section, identify a production program running on the mainframe device, compare the production program to the deployment package to identify a set of synchronization errors, resolve the synchronization errors, and deploy the deployment package to the mainframe device upon resolving the set of synchronization errors.