Abstract: Provided is a process, including: obtaining test data that quantifies a patient's cardiovascular status, the test data specifying patient attributes in a plurality of cardiovascular dimensions of the patient; determining a plurality of normalized differences between the test data and target criteria in each of the cardiovascular dimensions; determining predicted-effect vectors of each of a plurality of different classes of pharmaceuticals; determining an aggregate score for each respective class of pharmaceuticals among the different classes of pharmaceuticals based on values of the corresponding predicted-effect vectors; ranking the different classes of pharmaceuticals based on the aggregate scores; and outputting a recommended sequence of pharmaceuticals to administer.

Abstract: Provided is a process, including: obtaining test data that quantifies a patient's cardiovascular status, the test data specifying patient attributes in a plurality of cardiovascular dimensions of the patient; determining a plurality of normalized differences between the test data and target criteria in each of the cardiovascular dimensions; determining predicted-effect vectors of each of a plurality of different classes of pharmaceuticals; determining an aggregate score for each respective class of pharmaceuticals among the different classes of pharmaceuticals based on values of the corresponding predicted-effect vectors; ranking the different classes of pharmaceuticals based on the aggregate scores; and outputting a recommended sequence of pharmaceuticals to administer.

Abstract: Apparatus and methods are described herein for multiple single level security (MSLS) domains including, but not limited to, a secure kernel hypervisor (SKH). The SKH configures a single multi-tenant cloud to host the MSLS domains. A cloud orchestration system (COS) configures the single multi-tenant cloud to set up a plurality of separate virtual work packages (VWPs) for the MSLS domains. A key management system (KMS) is configured to manage security objects associated with the MSLS domains.

Abstract: Provided is a process, including: obtaining test data that quantifies a patient's cardiovascular status, the test data specifying patient attributes in a plurality of cardiovascular dimensions of the patient; determining a plurality of normalized differences between the test data and target criteria in each of the cardiovascular dimensions; determining predicted-effect vectors of each of a plurality of different classes of pharmaceuticals; determining an aggregate score for each respective class of pharmaceuticals among the different classes of pharmaceuticals based on values of the corresponding predicted-effect vectors; ranking the different classes of pharmaceuticals based on the aggregate scores; and outputting a recommended sequence of pharmaceuticals to administer.

Abstract: Provided is a process that includes: obtaining, with an artificial intelligence (AI) application executed by a computer system, information about a current patient condition related to heart failure; inputting, with the computer system, at least some of the obtained information about the patient condition into respective pharmaceutical-specific models to obtain candidate classes of pharmaceuticals and their respective priority scores; inputting, with the computer system, into an expert system of the AI application, the candidate classes of pharmaceuticals and their respective priority scores and, in response, determining an updated prescription.

Abstract: Provided is a process, including: obtaining test data that quantifies a patient's cardiovascular status, the test data specifying patient attributes in a plurality of cardiovascular dimensions of the patient; determining a plurality of normalized differences between the test data and target criteria in each of the cardiovascular dimensions; determining predicted-effect vectors of each of a plurality of different classes of pharmaceuticals; determining an aggregate score for each respective class of pharmaceuticals among the different classes of pharmaceuticals based on values of the corresponding predicted-effect vectors; ranking the different classes of pharmaceuticals based on the aggregate scores; and outputting a recommended sequence of pharmaceuticals to administer.

Abstract: Apparatus and methods are described herein for multiple single level security (MSLS) domains including, but not limited to, a secure kernel hypervisor (SKH). The SKH configures a single multi-tenant cloud to host the MSLS domains. A cloud orchestration system (COS) configures the single multi-tenant cloud to set up a plurality of separate virtual work packages (VWPs) for the MSLS domains. A key management system (KMS) is configured to manage security objects associated with the MSLS domains.

Abstract: Apparatus and methods are described herein for multiple single level security (MSLS) domains including, but not limited to, a secure kernel hypervisor (SKH). The SKH configures a single multi-tenant cloud to host the MSLS domains. A cloud orchestration system (COS) configures the single multi-tenant cloud to set up a plurality of separate virtual work packages (VWPs) for the MSLS domains. A key management system (KMS) is configured to manage security objects associated with the MSLS domains.

Abstract: Apparatus and methods are described herein for multiple single level security (MSLS) domains including, but not limited to, a secure kernel hypervisor (SKH). The SKH configures a single multi-tenant cloud to host the MSLS domains. A cloud orchestration system (COS) configures the single multi-tenant cloud to set up a plurality of separate virtual work packages (VWPs) for the MSLS domains. A key management system (KMS) is configured to manage security objects associated with the MSLS domains.