International Business Machines Corporation

Boston Scientific Neuromodulation Corporation

University of Illinois

Sara E Berger

James R Kozloski

Anup Kalia

Jeffrey L Rogers

Jeffrey Rogers

Systems and techniques are disclosed to establish programming of an implantable electrical neurostimulation device for treating pain of a human subject, through the use and adjustment of analgesic stimulation parameters based on trust dynamics and trust measurements. In an example, the system to establish programming of the neurostimulation device performs operations that: determine a trust measurement value that is derived from results of at least one commitment made with a human subject, via observable interactions; determine a modification of at least one neurostimulation programming parameter, based on the trust measurement value; and to cause the implantable neurostimulation device to implement the modification of the at least one neurostimulation programming parameter. Further examples are provided to produce and track the trust measurement value, as well as identify a pain susceptibility value and determine a receptiveness to analgesic effects based on these and other trust dynamics.

Adjustment of analgesic stimulation parameters based on trust dynamic measurements

Techniques regarding autonomously updating a participation status of an entity with regards to a clinical trial 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 comprise status component that can update a participation status of an entity regarding a clinical trial based on a trust disposition value. The trust disposition value can be determined using machine learning technology and can be indicative of an expected enrichment contribution associated with the participation status.

Updating a clinical trial participation status based on a measure of trust dynamics

Techniques regarding autonomously updating the status of a medical procedure 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 comprise a procedure component that can update a status of a medical procedure regarding an entity based on a trust disposition value derived using machine learning technology. The trust disposition value can be indicative of an expected efficacy associated with the medical procedure.

Assessing a medical procedure based on a measure of trust dynamics

Techniques regarding autonomously updating the status of a prescription 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 comprise a prescription component that can update a status of a prescription associated with an entity based on a trust disposition value. The trust disposition value can be determined using machine learning technology and can be indicative of an expected effectiveness of the prescription.

Updating a prescription status based on a measure of trust dynamics

Techniques regarding autonomously controlling the delivery of one or more chemical compounds 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 comprise a compound component can identify a chemical compound mixture to be distributed to an entity based on a trust disposition value. The trust disposition value can be determined using machine learning technology and is indicative of an expected effectiveness of the chemical compound mixture with regards to the entity.

Delivering a chemical compound based on a measure of trust dynamics

Techniques regarding autonomously determining an entity's susceptibility towards one or more treatment services 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 comprise an assessment component that can determine a susceptibility disposition value that measures a susceptibility of an entity to a treatment service based on a trust disposition value. The trust disposition value can be determined based on a communication with the entity using machine learning technology.

Growing community of inventors

White Plains, NY, United States of America

Sara E Berger