International Business Machines Corporation

Unicore Communications, Inc.

Intel Corporation

Microsoft Technology Licensing, LLC

Ge Medical Systems Global Technology Company, LLC

Ge Precision Healthcare LLC

China University of Mining and Technology

Wuhan Changsheng Mine Security Technology Limited

Institute of Pharmacology and Toxicology Academy of Military Medical Sciences P.l.a.

Gang Hu

Guo Tong Xie

Wen Sun

Jing Li

Jing Mei

Xue Qiao Hou

Bo Li

Yi Qin Yu

Shi Wan Zhao

Yue Pan

Haifeng Liu

Eryu Xia

En Liang Xu

Bi Bo Hao

Lei Huang

Tao Liu

Achille Belly Fokoue-Nkoutche

Kavitha Srinivas

Wei Shen

Jian Min Jiang

Anastasios Kementsietsidis

Hui-I Hsiao

Feng Cao

Zhao Ming Qiu

Kongzhe Chen

Qian Qian

Xianfa Fang

Wei Liu

Qiang Wu

Liu Liu

Xin Yang

Hai Feng Wang

Changliang Wang

Chen Wang

Li Ping Yang

Dong Hui Liu

Zhong Xian Li

Li Li Ma

Lin Wang

Lintao Zhang

Yadong Li

Lidong Zhou

Ping Zhang

Yunbiao Lin

Yifan Zeng

Lijun Liu

Xing Zhi Sun

Donald T Tang

Changhua Sun

Ming Wu

Hai Feng Liu

Liuhong Yun

Yong Ren

Zhaonan Sun

Sheng Liu

Chunsheng Liu

Bibo Hao

Rifang Yang

Fengjuan Tao

Jingjing Tao

Rusheng Zhao

Yuan Yan

Yahong Wang

Weijia Shen

Fulin Li

Xiaomin Yan

Gaoxian Zhang

Huayang Guo

Tisheng Chen

Huasong Feng

Xingchun Tang

Huamei He

Wenyu Cui

Qixiu Gao

Chaoliang Long

Xinqiang Lu

Xiao Yuan Wang

Disclosed is a system and a method of transient electromagnetic advanced detection. The system includes a detection host, an electromagnetic signal transmitter, a probe, and a communication device. The system and method of transient electromagnetic advance detection disclosed by examples of the present disclosure can realize an early-warning through a transient electromagnetic advance detection in a borehole while drilling the borehole in a tunnel or a roadway.

System and method of transient electromagnetic advanced detection

A method of determining position includes observing a first signal from a first source at a first epoch. The method includes observing a second signal from the first source at a second epoch. The method includes observing a third signal from a second source at the first epoch. The method includes observing a fourth signal from the second source at the second epoch. The method includes generating a first set of comparison data based on the first signal and the second signal. The method includes generating a second set of comparison data based on the third signal and the fourth signal. The method includes determining whether cycle-slip exists based on the first set of comparison data and the second set of comparison data. The method includes determining a current position of a standalone global navigation satellite system (GNSS) receiver in response to a determination that cycle-slip does not exist.

Method, apparatus for carrier-phase cycle-slip detection and repair

A method, device, and computer program storage product for generating a query to extract clinical features into a set of electronic medical record (EMR) tables based on clinical knowledge. A knowledge tree is constructed according to a set of clinical knowledge data. An EMR graph corresponding to a set of EMR tables is obtained. The EMR graph comprises at set of table nodes and a set of attribute nodes. The set of table nodes and the set of attribute nodes represent a structure of each EMR table in the set of EMR tables and a reference relationship among attributes of set of EMR tables. A plurality of sub-queries is generated based on the knowledge tree and the EMR graph. At least one query is generated by combining the plurality of sub-queries according to the knowledge tree.

Automatic knowledge-based feature extraction from electronic medical records

Systems, computer-implemented methods and/or computer program products that facilitate predicting personalized risks based on intrinsic factors and extrinsic factors are provided. In one example, a computer-implemented method comprises: collecting, by a system operatively coupled to a processor, intrinsic factors and extrinsic factors associated with infectious diseases; generating, by the system, a probabilistic model based on the intrinsic factors and extrinsic factors, wherein the model incorporates node characteristics into infection probability; and refining, by the system, the model through concurrently learning respective node thresholds and hidden infection network structure of the model.

Personalized risk prediction based on intrinsic and extrinsic factors

A computer implemented method identifies guidelines through use of a neural network by a remote guideline server. A client computer transmits instructions to the remote guideline server to retrieve and evaluate multiple candidate guidelines. The remote guideline server utilizes a neural network to identify a string of terms found in each of the multiple candidate guidelines that match one or more strings of terms from a model guideline; to identify a semantic concept of each of the multiple candidate guidelines that matches one or more semantic concepts from the model guideline; and to identify a structural pattern of each of the multiple candidate guidelines that matches one or more structural patterns of the model guideline. The candidate guidelines that match the model guideline are then sent from the remote guideline server to the client computer.

Remote neural network processing for guideline identification

Patient treatment may be optimized using Recurrent Neural Network (RNN) based state simulation and Reinforcement learning (RL) techniques to simulate future states and actions. A RNN state simulator and a RL action generator may be trained using patient data such as historical states and actions. The RL action generator may be optimized by applying the RNN state simulator to simulating future states and applying the RL action generator to generate recommended actions based on the simulated future states. This process may be iteratively performed until a computational convergence is reached by the RL action generator which may indicate that the RL action generator has been optimized. A patient state may be fed into the optimized RL action generator to generate an optimal recommended treatment action.

Optimizing patient treatment recommendations using reinforcement learning combined with recurrent neural network patient state simulation

Techniques are provided for enhancement of edges in image frames using depth information. A methodology implementing the techniques according to an embodiment includes receiving a color image frame and a depth map frame. The method also includes generating a sharpness mask to control the application of image sharpening to the color pixels. The sharpness mask is based on the value of depth pixels corresponding to the color pixels; and on properties of the depth camera that generated the color image frame, including depth of field, focal distance, and hyperfocal distance. The method further includes calculating sharpness strength for the color pixels. The sharpness strength is proportional to the value of the depth pixel corresponding to the color pixel. The method further includes applying a sharpening filter to the color image frame to enhance edge image features. The sharpening filter is based on the sharpness mask and the sharpness strength.

Enhancement of edges in images using depth information

A method, system, and computer program product, include obtaining a plurality of training sets of samples and a plurality of testing sets of samples from a data set of clinical records, the plurality of training sets of samples and the corresponding plurality of testing sets of samples including different samples of the data set, determining statistical significance for a plurality of risk factors of a model from the plurality of training sets of samples, determining a plurality of performance metrics of the model from the plurality of testing sets of samples, and determining an evaluation metric of the plurality of risk factors for the model based on the statistical significance and the plurality of performance metrics, the evaluation metric being for improving accuracy of the model.

System, method and computer program product for evaluation and identification of risk factor

A standalone GNSS receiver saves at each epoch a position and observables based on one or more signals. A reference position associated with a reference epoch is saved with reference observables. At a later epoch, the current position is determined by reference to the reference position and the reference epoch by performing a real time kinematic process. When cycle slip and/or signal lock has occurred, an ambiguity resolution is performed in real time kinematic. A standalone GNSS receiver with ambiguity resolution and real time kinematic at a current epoch achieves centimeter-level position accuracy by fixing ambiguities to integer and performing real time kinematic upon signal restoration. The saved reference data and coordinate serve as a reference station until signal restoration.

Real-time kinematic using standalone global navigation satellite system receiver

The present invention provides a movable patient table, comprising a table body, a first operating member, a locking member and a transfer member. The first operating member comprises a first operating part. Two ends of the locking member are respectively pivoted to the table body and the first operating member. The transfer member comprises a transfer part and a contact part, the transfer part is pivoted to the first operating member, and a pivoting point pivoted to the table body is provided between the transfer part and the contact part; and in a process that the first operating part is driven to be lowered down from a first released position to a locked position, the locking member and the transfer member respectively rotate around pivoting points with the table body until a pivoting point between the locking member and the table body, a pivoting point between the locking ember and the first operating member and a pivoting point between the transfer part and the first operating member are located on the same straight line, and the contact part rotates to be in contact with a movement plane of the table body.

Movable patient table

Combination therapies are automatically discovered that provide statistically significantly greater protection against a specific outcome, compared to therapies with fewer treatments. A dataset is received that associates each of a plurality of respective individual treatments with a corresponding outcome and a corresponding set of confounding factors. A plurality of new potential combination therapies are combined iteratively. The received dataset is used to automatically identify at least one candidate combination therapy of the new potential combination therapies that provides a statistically significantly greater protection against an outcome with reference to each of the plurality of respective individual treatments.

Automatically identifying statistically significant combination therapies from clinical data

Method and system for automatic knowledge-based feature extraction from electronic medical records

A method for automatically generating a semantic mapping for a relational database RDB includes obtaining a first semantic mapping from a first RDB to an ontology of linked data; obtaining a schema mapping from the first RDB to a second RDB; and generating a second semantic mapping from the second RDB to the ontology of the linked data based on the first semantic mapping and the schema mapping.

Automatically generating a semantic mapping for a relational database

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Beijing, China

Gang Hu