Abstract: Systems and methods for selecting a treatment regimen for a particular patient are provided. The treatment regimen is selected using a first data store including a first plurality of patient records for a first plurality of patients, and a second data store including efficacy rates of a plurality of treatment regimens against a plurality of infections and infection-causing pathogens. The system, or a user of the system, identifies a first infection of the particular patient and a first treatment regimen to be prescribed to treat the first infection. A second plurality of patient records is generated by identifying, in the first plurality of patient records of the first data store, patient records associated with diagnosis or treatment of the first infection. The second plurality of patient records are appended with efficacy rates for the first infection from the second data store.

Abstract: Systems and methods for selecting a treatment regimen for a particular patient are provided. The treatment regimen is selected using a first data store including a first plurality of patient records for a first plurality of patients, and a second data store including efficacy rates of a plurality of treatment regimens against a plurality of infections and infection-causing pathogens. The system, or a user of the system, identifies a first infection of the particular patient and a first treatment regimen to be prescribed to treat the first infection. A second plurality of patient records is generated by identifying, in the first plurality of patient records of the first data store, patient records associated with diagnosis or treatment of the first infection. The second plurality of patient records are appended with efficacy rates for the first infection from the second data store.

Abstract: Described herein are example methods and systems for neuro-behavioral relationships in dimensional geometric bedding (N-BRIDGE), which includes a comprehensive, data-driven analytic framework for mapping the multi-dimensional relationships between neural and behavioral features in humans N-BRIDGE allows mapping of variations along newly-defined data-driven behavioral dimensions that capture the geometry of behavioral/symptom variation to variation in specific neural features.

Abstract: Systems and methods for selecting a treatment regimen for a particular patient are provided. The treatment regimen is selected using a first data store including a first plurality of patient records for a first plurality of patients, and a second data store including efficacy rates of a plurality of treatment regimens against a plurality of infections and infection-causing pathogens. The system, or a user of the system, identifies a first infection of the particular patient and a first treatment regimen to be prescribed to treat the first infection. A second plurality of patient records is generated by identifying, in the first plurality of patient records of the first data store, patient records associated with diagnosis or treatment of the first infection. The second plurality of patient records are appended with efficacy rates for the first infection from the second data store.

Abstract: Systems and methods for selecting a treatment regimen for a particular patient are provided. The treatment regimen is selected using a first data store including a first plurality of patient records for a first plurality of patients, and a second data store including efficacy rates of a plurality of treatment regimens against a plurality of infections and infection-causing pathogens. The system, or a user of the system, identifies a first infection of the particular patient and a first treatment regimen to be prescribed to treat the first infection. A second plurality of patient records is generated by identifying, in the first plurality of patient records of the first data store, patient records associated with diagnosis or treatment of the first infection. The second plurality of patient records are appended with efficacy rates for the first infection from the second data store.

Abstract: An intelligent agent monitors operation of at least one software virtualized network (VN). Context information associated with the VN is used to analyze a state of the VN. At least one configuration change is caused to the VN in response to analysis of the state of the VN. A change is identified to the state of the VN caused by the configuration change. A determination is made as to whether or not the change to the state of the VN is an improvement to operation of the VN. A response to the determination is made by causing at least one other configuration change to the VN.

Abstract: A system may allow for generic end user mobile devices to be operated using a virtualized personal device framework. The virtualized personal device framework may provide for a collective intelligence network platform that allows offloading of heavy computing processes onto virtual instance in a cloud network and enables crowd sourcing services for smart cities that may provide smart emergency services in which end-users collaborate.

Abstract: An intelligent agent monitors operation of at least one software virtualized network (VN). Context information associated with the VN is used to analyze a state of the VN. At least one configuration change is caused to the VN in response to analysis of the state of the VN. A change is identified to the state of the VN caused by the configuration change. A determination is made as to whether or not the change to the state of the VN is an improvement to operation of the VN. A response to the determination is made by causing at least one other configuration change to the VN.

Abstract: Aspects of the subject disclosure may include, for example, a process or apparatus for receiving, by a processing system including a processor, cell traffic reports for cells of a radio communication network, performing a reconfiguration analysis to identify reconfiguration information to reconfigure the radio communication network according to changing network conditions, and communicating the reconfiguration information defining a new cell configuration for the cells of the radio communication network and communicating information defining a new reconfiguration time for the cells to substantially synchronously switch to communicating according to the reconfiguration information. The receiving the cell traffic reports, the performing the reconfiguration analysis and the communicating the reconfiguration information occur in substantially real time. Other embodiments are disclosed.

Abstract: A method may include a processing system having at least one processor for receiving a first machine learning model, the first machine learning model in a first format associated with a first development environment, adapting the first machine learning model to a containerized environment, validating the first machine learning model according to at least one validation criterion associated with a repository, and publishing the first machine learning model to the repository.

Abstract: A method is disclosed for cooling a heat transfer fluid circulating in a cooling circuit including a chiller. The method includes installing on the circuit a vacuum housing having a heat exchange conduit extending therethrough and partially filled with a coolant and an atmosphere and pre-cooling the atmosphere and coolant within the vacuum housing to a pre-cooling temperature of between 35 and 60 degrees Fahrenheit using a conventional cooling system. Thereafter the pressure in the vacuum housing is reduced to between 1 and 500 millitorr until an initial cooling temperature in the range of of ?50 to 35 degrees Fahrenheit is reached and the heat transfer fluid is then circulated through the heat exchange conduit and to the chiller and back. The pressure reduction in is obtained by selectively connecting the vacuum housing to a larger vacuum reservoir which is connected to a vacuum pump.

Abstract: A system can obtain a labelled data set, including historic video data and labelled events. The system can divide the labelled data set into historic training/testing data sets. The system can determine, using the historic training data set, a plurality of different parameter configurations to be used by a video encoder to encode a video that includes a plurality of video frames. Each parameter configuration can include a group of pictures (“GOP”) size and a scenecut threshold. The system can calculate an accuracy of event detection (“ACC”) and a filtering rate (“FR”) for each parameter configuration. The system can calculate, for each parameter configuration of the plurality of different parameter configurations, a harmonic mean between the ACC and the FR. The system can then select a best parameter configuration of the plurality of different parameter configurations based upon the parameter configuration that has the highest harmonic mean.

Abstract: An intelligent agent monitors operation of at least one software virtualized network (VN). Context information associated with the VN is used to analyze a state of the VN. At least one configuration change is caused to the VN in response to analysis of the state of the VN. A change is identified to the state of the VN caused by the configuration change. A determination is made as to whether or not the change to the state of the VN is an improvement to operation of the VN. A response to the determination is made by causing at least one other configuration change to the VN.

Abstract: A method may include a processing system having at least one processor for receiving a first machine learning model, the first machine learning model in a first format associated with a first development environment, adapting the first machine learning model to a containerized environment, validating the first machine learning model according to at least one validation criterion associated with a repository, and publishing the first machine learning model to the repository.

Abstract: A system may allow for generic end user mobile devices to be operated using a virtualized personal device framework. The virtualized personal device framework may provide for a collective intelligence network platform that allows offloading of heavy computing processes onto virtual instance in a cloud network and enables crowd sourcing services for smart cities that may provide smart emergency services in which end-users collaborate.

Abstract: A method may include obtaining a state diagram of a software management system, wherein the software management system manages at least a first software and configuring a license usage management system based on the state diagram.

Abstract: A system may allow for generic end user mobile devices to be operated using a virtualized personal device framework. The virtualized personal device framework may provide for a collective intelligence network platform that allows offloading of heavy computing processes onto virtual instance in a cloud network and enables crowd sourcing services for smart cities that may provide smart emergency services in which end-users collaborate.

Abstract: Devices, computer-readable media, and methods for submitting a modified voice input to a service based upon a user intent determined from a voice input in accordance with a voice interface of the service are disclosed. A processing system including at least one processor may obtain a voice input of a user, determine an intent from the voice input, identify a first service, from among a plurality of services, in accordance with the intent, and formulate a first modified voice input from the voice input in accordance with a voice interface of the first service, where each of the services is associated with one of a plurality of different voice interfaces. The processing system may further submit the first modified voice input to the first service, obtain a first voice response from the first service, and present a voice output to the user in accordance with the first voice response.

Abstract: A device and a system, based upon Deep Optical Scanning (DEOS), for the detection of certain cancers such as breast cancer and the determination of their response to therapy. DEOS is based upon the nonlinear optical interaction of incident laser generated light with tissue. The cancers may either be subsurface or on the surface. The system includes hardware and software components that form subsystems including: an Optical Electronic Subsystem, a Digitization Subsystem, a Parameter Computation Subsystem, an Archive, an Artificial Intelligence Subsystem, and a Presentation Subsystem. The device can be made portable and is non-invasive in its application to a patient. The system can be integrated into a hybrid architecture with other imaging techniques used for the detection of cancers.

Abstract: Systems and methods for selecting a treatment regimen for a particular patient are provided. The treatment regimen is selected using a first data store including a first plurality of patient records for a first plurality of patients, and a second data store including efficacy rates of a plurality of treatment regimens against a plurality of infections and infection-causing pathogens. The system, or a user of the system, identifies a first infection of the particular patient and a first treatment regimen to be prescribed to treat the first infection. A second plurality of patient records is generated by identifying, in the first plurality of patient records of the first data store, patient records associated with diagnosis or treatment of the first infection. The second plurality of patient records are appended with efficacy rates for the first infection from the second data store.