International Business Machines Corporation

Utopus Insights, Inc.

Shilpa N Mahatma

Francisco Phelan Curbera

Gigi Y C Yuen-Reed

Rachita Chandra

Arun Hampapur

Yajuan Wang

Italo Buleje

Fang Lu

Hongfei Li

Shubir Kapoor

Zhong Bo Jiang

Gigi Yuen-Reed

Jingwei Yang

Kevin N Tran

Wei Sun

Wei Shan Dong

Ajay Mohindra

Jayant R Kalagnanam

Aleksandra Mojsilovic

Shahram Ebadollahi

Ock Kee Baek

Rose Marie Williams

Lexing Xie

Piyush Madan

Andrew J Davenport

Houtan Aghili

Frank D Fenhagen, Iv

Sundar Saranathan

Marie Angelopoulos

Tarun Kumar

Vijay Krishnarao Naik

Steven I Ross

Bonnie Kathryn Ray

Naoki Abe

Balaji Krishnapuram

Karthikeyan Natesan Ramamurthy

Faisal Farooq

Aurelie C Lozano

Dennis Wei

Jing Fu

Floyd S Kelly

Michal Ozery-Flato

Brian Arffa

Rose M Williams

Michael G Gemmell

David M Loehr

Brendan Shea

Sharon M Hensley Alford

Mehmet F Candas

Leemor M Yuravlivker

A mechanism is provided in a data processing system comprising at least one processor and at least one memory, the at least one memory comprising instructions executed by the at least one processor to cause the at least one processor to implement a healthcare analytics management system. A healthcare analytics development sub-system of the healthcare analytics management system develops an analytics pipeline of a set of analytics assets for a selected healthcare based on a set of business needs for a healthcare analytics client and a healthcare analytics model based on the set of analytics assets and the set of business needs. The healthcare analytics model links to the analytics pipeline. A model deployment module of a healthcare analytics operation sub-system of the healthcare analytics management system deploys the healthcare analytics model on a set of computing devices of the selected healthcare consumer. Responsive to a model monitoring module of the healthcare analytics operation sub-system detecting a performance deviation of the deployed healthcare analytics model for performance deviation from the set of business needs for the healthcare analytics client, a model feedback module of the healthcare analytics operation sub-system determines improvement needs for the healthcare analytics model. The model feedback module feeds the improvement needs back to the healthcare analytics development sub-system. The healthcare analytics development sub-system customizes the healthcare analytics model based on the improvement needs.

Scalable and traceable healthcare analytics management

A method for creating a spatio-temporal schedule includes receiving a set of available work crews and a set of workorders to be scheduled, sequencing the set of workorders, wherein each workorder of the set of workorders is associated with a geographic location, a start time and an end time, and iterating through the set of available work crews, assigning a plurality of workorders of the set of workorders fully allocating a current crew before selecting a next crew, until all work crews are fully allocated and/or all workorders are assigned, wherein the assignment of workorders for a given work crew generates a route comprising the plurality of workorders.

Spatio-temporal approach to scheduling field operations

A mechanism is provided to implement a healthcare analytics management system. A healthcare analytics development sub-system develops an analytics pipeline of a set of analytics assets for a selected healthcare based on a set of business needs for a healthcare analytics client and a healthcare analytics model based on the set of analytics assets and the set of business needs. A model deployment module of a healthcare analytics operation sub-system deploys the healthcare analytics model on a set of computing devices of the selected healthcare consumer. Responsive to detecting a performance deviation of the deployed healthcare analytics model from the set of business needs, a model feedback module determines improvement needs for the healthcare analytics model. The model feedback module feeds the improvement needs back to the healthcare analytics development sub-system. The healthcare analytics development sub-system customizes the healthcare analytics model based on the improvement needs.

A mechanism is provided in a data processing system to implement a feature extraction tool for graphical user interface based feature extraction. The feature extraction tool receives selection by a user of a dataset from which features are to be extracted. The feature extraction tool loads a plurality of feature definitions. The feature extraction tool generates a graphical user interface that allows the user to add features from the plurality of features to a feature file. The feature extraction tool presents the graphical user interface to the user and receives user selection of at least one feature to be added to the feature file. The feature extraction tool generates the feature file based on the user selection of the at least one feature.

Graphical user interface based feature extraction application for machine learning and cognitive models

Embodiments of the present invention disclose a method, a computer program product, and a computer system for medication decision support. A computer generates one or more patient profiles detailing one or more patient health conditions and one or more medication profiles detailing one or more medication side effects. The computer then determines an association between the one or more patient health conditions and one or more medication side effects and quantifies the association as a conflict score. In addition, the computer determines whether the conflict score exceeds a threshold and, if so, the computer identifies and recommends an alternative medication having a lower conflict score.

Medication decision support

Embodiments of the present invention disclose a method, a computer program product, and a computer system for mapping components of non-distributed environments to distributed environments. A computer receives a data pipeline configured for a non-distributed environment and identifies one or more bottleneck components of the data pipeline. In addition, the computer converts data used in the pipeline to a format compatible with a distributed environment and installs the necessary computing libraries necessary for operating the pipeline within the distributed environment. The computer further converts the code of the pipeline to a code that is compatible with the distributed environment and optimizes components of the pipeline for use in the distributed environment.

Mapping components of a non-distributed environment to a distributed environment

Modularized data processing systems and methods for its use are provided. Processing a current job can reuse data generated for a previously processed job to the extent the two share parameter configurations. Similarly, outputs of processing modules generated during processing the previously processed job can be used as inputs to processing modules processing a current job, if the two jobs share some parameter configurations.

Job management in data processing system

Methods and apparatus for identifying health trends via the identification of ambiguous food items via container identification may be provided by: receiving an image captured from a user device that includes a food item; identifying a food container present in the image; identifying a utensil present in the image; determining a cluster of food items from a food recognition database corresponding to the food container and to the utensil; selecting a candidate food item from the cluster based on a confidence score of the candidate food item matching the food item; and adding the candidate food item to a dietary log associated with the user device.

Health trends identification

A computing system initializes a first frontier to be a root of a multi-dimensional hierarchical data structure representing an entity. The system acquires first data corresponding to the first frontier. The system performs modeling on the first data to obtain a first model and a corresponding first statistic. The system expands a dimension of the first frontier. The system gathers second data corresponding to the expanded frontier. The system applies the data modeling on the second data to obtain a second model and a corresponding second statistic. The system compares the first statistic of the first model and the second statistic of the second model. The system sets the second model to be the first model in response to determining that the second model statistic is better than the first model statistic. The system outputs the first model.

Casual modeling of multi-dimensional hierarchical metric cubes

Embodiments of the present invention provide methods, computer program products, and a system for determining and providing health risk alerts. Embodiments of the present invention can be used to collect numbers entered by a user, which in turn are used to determine the health risks of the behavior of the user. Embodiments of the present invention can be used to issue alerts to a person of interest based, at least in part, on the number strings entered by the user.

Health trend identification

A method, system and computer program product for detecting anomalies in a metering system. In one embodiment, data representing usage of a defined commodity are collected from meters, and the data collected over a given time period are analyzed to identify any of the meters showing at least one defined type of anomalous usage pattern. For each of the meters showing an anomalous usage patterns, an anomaly score is determined for the usage pattern shown, and the anomaly scores are used to rank the meters. In one embodiment, the collected data are analyzed to identify any of the meters showing one or more of a group of types of anomalous patterns including meter-no-reading, meter-by-pass, and meter-silting patterns. Embodiments of the invention utilize time series techniques and data analysis on meter reading data. Further, embodiments of the invention require no additional installation of equipment or sensors.

Anomaly detection using usage data for metering system

An application as a service provided in a secure environment. A sandbox in a user's computing environment may be created. An application may be downloaded to the user's computing environment to run within the sandbox. Data sources associated with the user's computing environment may be searched and connectivity established with data registry of the data sources based on data description received with the application. The application may be run within the sandbox using the established connectivity. Metering may be performed to monitor usage of the application at the user's computing environment.

Healthcare as a service&#x2014;downloadable enterprise application

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Mohegan Lake, NY, United States of America

Shilpa N Mahatma