International Business Machines Corporation

Boston Scientific Neuromodulation Corporation

University of Illinois

Kyndryl, Inc.

Anup Kalia

Maja Vukovic

Jin Xiao

Jinho Hwang

John Joseph Rofrano

James R Kozloski

Jeffrey L Rogers

Sara E Berger

Chen Lin

Muhammed Fatih Bulut

Raghav Batta

Saurabh Sinha

Nikolaos Anerousis

Sai Zeng

Constantin Mircea Adam

Clifford A Pickover

Jie Ma

Ya Bin Dang

Milton H Hernandez

Frederick Y Wu

Rohit Madhukar Khandekar

Valentina Salapura

Komminist S Weldemariam

Yu Deng

Elizabeth Daly

Vugranam Chakravarthy Sreedhar

Brian L Peterson

Oznur Alkan

Richard Baxter Hull

Lijun Mei

Lisa M Chavez

Virginia Mayo Policarpio

Michael S Gordon

Zhong Su

Bei Chen

Li Jun Mei

Honglei Guo

Rahul Nair

Senthil Kumar Kumarasamy Mani

Zhili Guo

Changhua Sun

Frederick Yung-Fung Wu

Mihir Choudhury

Hongtan Sun

Malik Jackson

Tarek Sakakini

Lambert Pouguem Wassi

Shawn Dsouza

Technology for applying artificial intelligence to decide when to, and/or when not to, send a consumer of a computer system a communication recommending that the computer system be revised to include a more recent version of at least one of the following: a hardware component (for example, microprocessor(s)) and/or a software component (for example, an updated version of an app). The computer system, that is subject to modernization, may be owned outright by the consumer, or it may be purchased as a service (for example, infrastructure as a service, software as a service, package of cloud services). Some embodiments focus on modernization recommendations specifically tailored to cloud orchestration software that deploys containers.

Artificial intelligence based application modernization advisory

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

Learning and correcting errors in text input fields to an artificial intelligence (AI) system includes receiving, by the AI system from a target system, an input text. The AI system executes a text processing operation on the input text by applying at least one transformer from a library of transformers to the input text to generate transformed text. At least one proposed correction to the input text is output by the AI system based on an analysis of the transformed text. Feedback data, associated with the at least one proposed correction, is then received from a user of the target system to iteratively learn, by the AI system, which of the transformers need be applied on future input text to accurately generate future proposed corrections on the future input text.

Syntactic and semantic autocorrect learning

Systems, computer-implemented methods, and computer program products to facilitate generation of microservices from a monolithic application based on runtime traces are provided. According to an embodiment, 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 a model component that learns cluster assignments of classes in a monolithic application based on runtime traces of executed test cases. The computer executable components can further comprise a cluster component that employs the model component to generate clusters of the classes based on the cluster assignments to identify one or more microservices of the monolithic application.

Generation of microservices from a monolithic application based on runtime traces

Systems, computer-implemented methods, and computer program products to facilitate modernization of an application are provided. According to an embodiment, 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 a determination component that determines one or more relevant surrounding contexts for a raw entity. The computer executable components also can comprise a matching component that matches the one or more relevant surrounding contexts with one or more known surrounding contexts of one or more known entities. The computer executable components further can comprise a type identification component that identifies an entity type for the raw entity based on the matching of the one or more relevant surrounding contexts with the one or more known surrounding contexts.

Modernization of an application for related image generation

Techniques regarding discovering configuration information for one or more computer applications 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 configuration component that can discover configuration information associated with a containerized computer application. The configuration information can be characterized by a set of environment attributes extracted by querying a source code of the containerized computer application.

Configuration discovery of computer applications

Techniques are described for providing live first aid response guidance using a machine learning based cognitive aid planner. In one embodiment, a computer-implemented method is provided that comprises classifying, by a system operatively coupled to a processor, a type of an injury endured by a patient. The method further comprises, employing, by the system, one or more machine learning models to estimate a risk level associated with the injury based on the type of the injury and a current context of the patient.

Providing live first aid response guidance using a machine learning based cognitive aid planner

A technique relates to natural language automation to implement service requests. An intent of a service request is determined by accessing a knowledge base, the knowledge base being configured for dynamic discovery of dependencies related to configuration items, the configuration item being among the configuration items, the configuration items being associated with concepts. An intent application programming interface (API) database comprising a specification is accessed, the specification describing parameters of APIs and associations that the APIs have with the concepts of the knowledge base. Associated parameters of an API associated with the intent of the service request are determined based on the intent API database. The API is caused to be executed to accomplish the service request.

Performing natural language based reasoning and automation by transforming a configuration management database to a knowledge base

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

Systems, computer-implemented methods, and computer program products that can facilitate extraction of named entities from document data to support automation applications are provided. According to an embodiment, 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 entity extraction component that extracts, using a first machine learning process, a first data entity and a second data entity from document data indicative of a textual information. The computer executable components can further comprise a relation extraction component that determines, using a second machine learning process, a relation between the first data entity and the second data entity to generate a knowledge data graph used to execute an application associated with natural language processing for the document data.

Extraction of named entities from document data to support automation applications

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Elmsford, NY, United States of America

Anup Kalia