Nec Corporation

Indiana University

The Ohio State University

Nec Laboratories America, Inc.

Xia Ning

Guofei Jiang

Junghwan Rhee

Bo Peng

Titus K Schleyer

Zhiyun Ren

Haifeng Chen

Hui Joyce Zhang

Zhenyu Wu

Zhichun Li

Kenji Yoshihira

Bing Bai

Yanjun Qi

Jun Wang

Zhiyun Qian

Xiao Bian

Titus Karl Ludwig Schleyer

Hongteng Xu

Pavel Kuksa

Disclosed embodiments include computer-implemented methods and systems that can efficiently generate highly relevant recommended search terms to clinicians. A hybrid collaborative filtering model recommends search terms for a specific patient to the clinician. The model draws on information from patients' clinical encounters and the searches that were performed during the clinical encounters. To generate recommendations, the model uses search terms which are (1) frequently co-occurring with the ICD codes recorded for the patient and (2) highly relevant to the most recent search terms. One variation of the model uses only the most recent ICD codes assigned to the patient. Another variation uses all ICD codes. Comprehensive experiments of embodiments of the methods and systems have demonstrate high levels of performance.

Systems and methods for providing health care search recommendations

Methods for generating a health management template for a patient condition including retrieving a healthcare template It corresponding to a patient condition, the healthcare template comprising a plurality of data fields, populating the data fields with patient data; and generating an updated healthcare template based on a user input, wherein the user input comprises at least one of a search request or a data option selection are disclosed. Systems are also disclosed.

Systems and methods for accessing, combining and collaborative filtering of information from multiple electronic health records

A method and system are provided for heterogeneous log analysis. The method includes performing hierarchical log clustering on heterogeneous logs to generate a log cluster hierarchy for the heterogeneous logs. The method further includes performing, by a log pattern recognizer device having a processor, log pattern recognition on the log cluster hierarchy to generate log pattern representations. The method also includes performing log field analysis on the log pattern representations to generate log field statistics. The method additionally includes performing log indexing on the log pattern representations to generate log indexes.

Heterogeneous log analysis

A system, method and computer program product for hierarchical sparse dictionary learning ('HiSDL') to construct a learned dictionary regularized by an a priori over-complete dictionary, includes providing at least one a priori over-complete dictionary for regularization, performing sparse coding of the at least one a priori over-complete dictionary to provide a sparse coded dictionary, using a processor, updating the sparse coded dictionary with regularization using at least one auxiliary variable to provide a learned dictionary, determining whether the learned dictionary converges to an input data set, and outputting the learned dictionary regularized by the at least one a priori over-complete dictionary when the learned dictionary converges to the input data set. The system and method includes, when the learned dictionary lacks convergence, repeating the steps of performing sparse coding, updating the sparse coded dictionary, and determining whether the learned dictionary converges to the input data set.

Hierarchical sparse dictionary learning (HiSDL) for heterogeneous high-dimensional time series

Methods and systems for process constraint include collecting system call information for a process. It is detected whether the process is idle based on the system call information and then whether the process is repeating using autocorrelation to determine whether the process issues system calls in a periodic fashion. The process is constrained if it is idle or repeating to limit an attack surface presented by the process.

Discovering and constraining idle processes

A system and method for profiling a request in a service system with kernel events including a pre-processing module configured to obtain kernel event traces from the service system and determine starting and ending communication pairs of a request path for a request. A learning module is configured to learn pairwise relationships between the starting and ending communication pairs of training traces of sequential requests. A generation module is configured to generate communication paths for the request path from the starting and ending communication pairs of testing traces of concurrent requests using a heuristic procedure that is guided by the learned pairwise relationships and generate the request path for the request from the communication paths. The system and method precisely determine request paths for applications in a distributed system from kernel event traces even when there are numerous concurrent requests.

System and method for profiling requests in service systems

Systems and methods are disclosed to perform relation extraction in text by applying a convolution strategy to determine a kernel between sentences; applying one or more semi-supervised strategies to the kernel to encode syntactic and semantic information to recover a relational pattern of interest; and applying a classifier to the kernel to identify the relational pattern of interest in the text in response to a query.

Systems and methods for semi-supervised relationship extraction

Growing community of inventors

Columbus, OH, United States of America

Xia Ning