Abstract: A medical knowledge database including medical knowledge information, medical diagnoses, and medical treatments, is used for machine learning for collaborative medical data metrics. Medical data is collected from a plurality of clinicians serving a first plurality of patients and assembling a medical knowledge database that includes medical knowledge information, medical diagnoses, and medical treatments. The medical knowledge database is a function of demographics and comprises a medical probabilistic rules graph. The medical knowledge database is augmented based on further medical data collected from a second plurality of clinicians. The further medical data is based on individual patient treatment outcomes collected by the second plurality of clinicians. Medical data from a further patient is applied to the medical probabilistic rules graph. A medical diagnosis is provided, based on the medical data applied from a further patient to the rules graph.

Abstract: A system includes a computer storage device to store a first and second set of information about individuals, and user interface design components. A computer server is coupled to the computer storage and is programmed to receive a request for a webpage from an individual's device and analyze the first and second set of information to predict differences in at least one key performance indicator for that individual. The server is further programmed to automatically select a user interface design component for presentation to the individual, automatically generate and transmit a first customized webpage with the selected user interface design component to the device, and in response to an interaction with the selected user interface design component on the first customized webpage, automatically generate and transmit a second customized webpage to the device to create a customized page flow.

Abstract: A system includes a computer storage device to store a first and second set of information about individuals, and user interface design components. A computer server is coupled to the computer storage and is programmed to receive a request for a webpage from an individual's device and analyze the first and second set of information to predict differences in at least one key performance indicator for that individual. The server is further programmed to automatically select a user interface design component for presentation to the individual, automatically generate and transmit a first customized webpage with the selected user interface design component to the device, and in response to an interaction with the selected user interface design component on the first customized webpage, automatically generate and transmit a second customized webpage to the device to create a customized page flow.

Abstract: A medical knowledge database including medical knowledge information, medical diagnoses, and medical treatments, is used for machine learning for collaborative medical data metrics. Medical data is collected from a plurality of clinicians serving a first plurality of patients and assembling a medical knowledge database that includes medical knowledge information, medical diagnoses, and medical treatments. The medical knowledge database is a function of demographics and comprises a medical probabilistic rules graph. The medical knowledge database is augmented based on further medical data collected from a second plurality of clinicians. The further medical data is based on individual patient treatment outcomes collected by the second plurality of clinicians. Medical data from a further patient is applied to the medical probabilistic rules graph. A medical diagnosis is provided, based on the medical data applied from a further patient to the rules graph.

Abstract: Disclosed are systems and methods to provide energy control via power-requirement analysis and power-source enablement. Both demand-side and supply-side techniques are used alone or in conjunction to determine an optimal number of power sources to supply power to one or more loads. When fluctuations in power requirements are present, measures such as decoupling less-critical loads in order to continue delivering power to critical systems and turning on and off power sources as needed to meet the current power demands of a system are implemented. Power sources are periodically deactivated by the system on a rotational basis such that all power sources wear evenly, prolonging the life of the equipment. A scalable architecture that allows the virtualization of power from the underlying hardware form factor is also provided.

Abstract: A system includes a computer storage device to store a first and second set of information about individuals, and user interface design components. A computer server is coupled to the computer storage and is programmed to receive a request for a webpage from an individual's device and analyze the first and second set of information to predict differences in at least one key performance indicator for that individual. The server is further programmed to automatically select a user interface design component for presentation to the individual, automatically generate and transmit a first customized webpage with the selected user interface design component to the device, and in response to an interaction with the selected user interface design component on the first customized webpage, automatically generate and transmit a second customized webpage to the device to create a customized page flow.

Abstract: Biological information and medical knowledge information are used for self-learning clinical intelligence. Medical knowledge information is assembled. Medical rules are generated based on the medical knowledge. The medical rules can be generated probabilistically. A plurality of risk models can be learned. The plurality of risk models are associated with a given disease based on patient attributes. A medical probabilistic rule graph is built based on the medical rules and the plurality of risk models. The building of the medical probabilistic rule graph is based on ordering the medical rules. Attributes from an individual patient are applied to the medical probabilistic rule graph. A diagnosis for the individual is generated from the attributes applied to the medical probabilistic rule graph. A treatment for the individual can be generated from the attributes applied to the medical probabilistic rule graph.

Abstract: Disclosed are systems and methods to provide energy control via power-requirement analysis and power-source enablement. Both demand-side and supply-side techniques are used alone or in conjunction to determine an optimal number of power sources to supply power to one or more loads. When fluctuations in power requirements are present, measures such as decoupling less-critical loads in order to continue delivering power to critical systems and turning on and off power sources as needed to meet the current power demands of a system are implemented. Power sources are periodically deactivated by the system on a rotational basis such that all power sources wear evenly, prolonging the life of the equipment. A scalable architecture that allows the virtualization of power from the underlying hardware form factor is also provided.