Abstract: Techniques regarding pain treatment are provided. For example, one or more embodiments described herein can comprise a system, which can comprise a memory that can store computer executable components. The system can also comprise a processor, operably coupled to the memory, and that can execute the computer executable components stored in the memory. The computer executable components can include: a data collection component that can determine at least one parameter associated with a pain perception of a subject, a computing component that can determine a relationship between the pain perception and the at least one parameter using artificial intelligence, and can determine a treatment for the subject based on the relationship; and a treatment component that can cause a device associated with the subject to apply at least a portion of the treatment.

Abstract: Embodiments for managing an as-a-service (aaS) computing system by a processor are provided. Input provided by at least one computing device to a cloud platform is monitored. Output provided by the cloud platform to the at least one computing device in response to the input provided by the at least one computing device is monitored. At least one local model is generated based on the input provided to the cloud platform and the output provided to the at least one computing device.

Abstract: Embodiments for managing an as-a-service (aaS) computing system by a processor are provided. Input provided by at least one computing device to a cloud platform is monitored. Output provided by the cloud platform to the at least one computing device in response to the input provided by the at least one computing device is monitored. At least one local model is generated based on the input provided to the cloud platform and the output provided to the at least one computing device.

Abstract: Techniques that facilitate three-dimensional (3D) delineation of tumor boundaries via one or more supervised machine learning algorithms are provided. An example embodiment includes a computer-implemented method that includes: extracting, by a computing system operatively coupled to a processor, one or more feature vectors from a time-series evolution of fluorescence distribution observed at a section of bodily tissue of interest, wherein the one or more feature vectors represent a physical model describing on-tissue dye dynamics of the section of bodily tissue; and generating, by the computing system, a classification attribute for the section of bodily tissue represented by the one or more feature vectors, wherein a pre-trained classifier designates the section of bodily tissue as a biopsy or a non-biopsy candidate through execution of the one or more supervised machine learning algorithms.

Abstract: One or more systems, computer-implemented methods and/or computer program products to facilitate a process to produce a specified electrical output are provided. A system can comprise a memory that stores computer executable components and a processor that executes the computer executable components stored in the memory. The computer executable components can comprise an inverse modeling component that can generate an entity-based model and can determine updated one or more electrostatics parameters based on feedback relative to application of an electrical stimulation therapy employing an initial one or more electrostatics parameters on the entity.

Abstract: Techniques regarding pain treatment are provided. For example, one or more embodiments described herein can comprise a system, which can comprise a memory that can store computer executable components. The system can also comprise a processor, operably coupled to the memory, and that can execute the computer executable components stored in the memory. The computer executable components can include: a data collection component that can determine at least one parameter associated with a pain perception of a subject, a computing component that can determine a relationship between the pain perception and the at least one parameter using artificial intelligence, and can determine a treatment for the subject based on the relationship; and a treatment component that can cause a device associated with the subject to apply at least a portion of the treatment.

Abstract: Techniques regarding pain treatment are provided. For example, one or more embodiments described herein can comprise a system, which can comprise a memory that can store computer executable components. The system can also comprise a processor, operably coupled to the memory, and that can execute the computer executable components stored in the memory. The computer executable components can include: a data collection component that can determine at least one parameter associated with a pain perception of a subject, a computing component that can determine a relationship between the pain perception and the at least one parameter using artificial intelligence, and can determine a treatment for the subject based on the relationship; and a treatment component that can cause a device associated with the subject to apply at least a portion of the treatment.

Abstract: Techniques regarding pain treatment are provided. For example, one or more embodiments described herein can comprise a system, which can comprise a memory that can store computer executable components. The system can also comprise a processor, operably coupled to the memory, and that can execute the computer executable components stored in the memory. The computer executable components can include: a data collection component that can determine at least one parameter associated with a pain perception of a subject, a computing component that can determine a relationship between the pain perception and the at least one parameter using artificial intelligence, and can determine a treatment for the subject based on the relationship; and a treatment component that can cause a device associated with the subject to apply at least a portion of the treatment.