International Business Machines Corporation

Samsung Electronics Co., Ltd.

Petrochina Company Limited

Guangdong Oppo Mobile Telecommunications Corp., Ltd.

Sunshine Lake Pharma Co., Ltd.

Yi Qin Yu

Guo Tong Xie

Jing Li

Haifeng Liu

Shi Lei Zhang

Wen Sun

Jing Mei

Lin Xu

Xingzhi Sun

Bi Bo Hao

Shiwan Zhao

Gang Hu

Eryu Xia

Yuan Zhou

Xu Min

Shao Chun Li

Yong Qin

Bibo Hao

Sui Jun Tong

Jian Wang

Yu Chen Zhou

Yingjun Zhang

Wei Shen

Jian Min Jiang

Rong Fu

Ping Zhang

Yue Pan

Xuan Zhang

Wei Gao

Xiaojun Wang

Xing Zhi Sun

Jiancun Zhang

Hao Guo

Bo Ma

Yadong Hu

Liang Chen

Hai Feng Liu

Yingying Jiang

Kang Chen

Shimin Jiang

Botao Cu

En Liang Xu

Xiaobing Wang

Zhenbo Luo

Runfeng Lin

Pingjun Li

Fusen Xiao

Xiangyu Zhu

Jihua Lin

Yan Fei Wang

Guangrong Zhang

Qi Ran

Shirong Zhang

Qi Liao

Han Liang

Xiaomin Lu

Xiao Fei Teng

Ying Xue Li

A computer implement method for domain adaptation. According to the method, training data from a target domain may be classified by using a group of source models of a source domain, where each of the source models is trained to classify data from the source domain. A first pseudo label indicating a category of the training data may be generated by aggregating classification results of the source models based on respective weights of the source models on predetermined data categories. A target model of the target domain may be trained based on the training data and the first pseudo label and the second pseudo label, where the target model is trained to classify data from the target domain.

Domain adaptation

Embodiments of the present disclosure relate to a method, system, and computer program product for domain adaptation. According to the method, a source model of a source domain is obtained, where the source model is trained to generate a label indicating a predicted category of data from the source domain. A training sample from a target domain is obtained, where the training sample comprises training data from the target domain and a true label indicating a true category of the training data from the target domain. A first label is generated for the training data by using the source model. The first label indicates a predicted category of the training data. A target model of the target domain is trained based on the training data, the true label and the first label.

The present disclosure relates to a method, system and computer program product for electronic health record (EHR) data synthetization. According to the method, an original EHR dataset X is captured. A latent space Z is generated from the original EHR dataset X, wherein dimensionality of Z is lower than that of X. A stochastic process prior module is applied to the latent space Z. Synthetic EHR dataset X' is reconstructed from the latent space Z after being applied with the stochastic process prior.

Electronic health record data synthesization

Aspects of the invention include a computer-implemented method including extracting a domain-specific object feature from a first image data, wherein the feature describes an object in the first image data. A domain-specific semantic meaning of text data is determined. The object feature is mapped to a portion of the text data, wherein the portion of the text data describes the object. A joint representation of the object and the portion of the text data is created. A second image data and a query directed towards an object in the second image data is received. An answer to the query is generated based on the joint representation.

Medical visual question answering

The disclosure provides a method for data instance processing. The method includes obtaining a set of data instances collected from a plurality of organizations. Each of the data instances includes at least one record formed in an organization that stores values of a plurality of attributes of the data instance. The method also includes dividing the set of data instances into groups, wherein data instances with conflicting values for the same attribute are divided into different groups. The method further includes subdividing data instances in each of the groups into clusters.

Cross-organization data instance matching

A method, a system and a computer program product may evaluate reduction of disease risk. Patient data of a patient may be received. A selection of a disease outcome may be received. A risk score that the patient will experience the selected disease outcome may be determined. The determining may use the patient data. Intervention options may be generated based on the patient data and by accessing a medical record data structure. An intervention effect for each of the intervention options may be determined. The intervention effect may change the risk score. The intervention effects may be compared. A recommendation of at least one of the intervention options may be provided based on the comparing of the intervention effects.

Evaluation of reduction of disease risk and treatment decision

A method for detecting deviations between an event log and a process model includes converting the process model into a probability process model, the probability process model comprising multiple nodes in multiple hierarchies and probability distribution associated with the multiple nodes, a leaf node among the multiple nodes corresponding to an activity in the process model; detecting differences between at least one event sequence contained in the event log and the probability process model according to a correspondence relationship; and identifying the differences as the deviations in response to the differences exceeding a predefined threshold; wherein the correspondence relationship describes a correspondence relationship between an event in one event sequence of the at least one event sequence and a leaf node in the probability process model.

Detecting deviations between event log and process model

The present application discloses an image processing method, apparatus, electronic device and computer readable storage medium. The image processing method comprises detecting a text region in an image to be processed, recognizing the text region to obtain a text recognition result. In this application, the text recognition in the image to be processed is realized, the recognition manner for the text in the image is simplified, and the recognition effect for the text is improved.

Image processing method, apparatus, electronic device and computer readable storage medium

Systems, computer-implemented methods and/or computer program products that facilitate providing treatment suggestions are described herein. In one example, a computer-implemented method comprises: generating, by a system operatively coupled to a processor, treatment directed graphs associated with a plurality of treatment regimens, wherein, in connection with generating respective treatment directed graphs, penalties are applied during weighting of respective regimens as a function of an associated confidence level; identifying a treatment directed graph that corresponds to the patient directed graph; and outputting a set of treatment suggestions associated with the treatment directed graph that corresponds to the patient directed graph.

Facilitating health intervention suggestion for disease mitigation and/or prevention

Techniques for augmenting relational databases with graph database capabilities are described. A graph database query requesting data from a graph database is received. The graph database includes a plurality of vertices and a plurality of edges. The graph database query is translated into a relational database query using one or more computer processors. The relational database query references a vertex table and an edge table in a relational database. Result data corresponding with the graph database query is retrieved from the relational database by executing the relational database query against the relational database.

Augmenting relational database engines with graph query capability

A system for decentralized privacy-preserving clinical data evaluation includes a plurality of sites of a decentralized private network, a memory device for storing program code, and at least one processor device operatively coupled to the memory device and configured to execute program code stored on the memory device to, for each of the local datasets, evaluate the local dataset using each of the local models to obtain one or more features related to a degree of outlierness, determine at least one outlier dataset based on the one or more features, and implement one or more actions based on the determination.

Decentralized privacy-preserving clinical data evaluation

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

A computer-implemented method, system, and computer program product are provided for enhanced search strategies. The method includes selecting, by a processor device, known candidate sources related to a search topic. The method also includes ranking, by the processor device, keyphrase candidates from the known candidate sources according to inter-topic weighting. The method additionally includes assembling, by the processor device, a search string of a predetermined number of top ranked keyphrase candidates. The method further includes generating, by the processor device, new candidate sources from a candidate source repository responsive to the search string. The method also includes defining, by the processor device, a candidate source pool by the known candidate sources and the new candidate sources to reduce user search times on computer interface devices.

Enhanced search construction and deployment

The present disclosure provides a method, apparatus and system for processing a case management model (CMM). According to an embodiment, there is provided a method for processing a CMM, the method includes: obtaining an existing CMM having a plurality of elements; obtaining a new CMM having at least one element; aligning an element of the new CMM to an element of the existing CMM according to match costs between the element of the new CMM and the plurality of elements of the existing CMM; and fusing the new CMM into the existing CMM based on the match cost between the aligned elements.

Case management model processing

Growing community of inventors

Beijing, China

Yi Qin Yu