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公开(公告)号：US10803144B2
公开(公告)日：2020-10-13
申请号：US14270498
申请日：2014-05-06
发明人： Jianying Hu , Robert K. Sorrentino , Fei Wang , Ping Zhang
摘要： A processor-implemented method, computer program product and system are provided for predicting drug-drug interactions based on clinical side effects. The method includes constructing a drug-drug interactions training dataset that includes pharmaceutical, pharmacokinetic or pharmacodynamics drug-drug interactions from multiple data sources for each of a plurality of drugs. The method also includes constructing side effect features for each of the drugs from side effects associated with the drugs. The method further includes building, using the drug-drug interactions training dataset, a drug-drug interactions classifier that predicts adverse drug-drug interactions for drug pairs derivable from the drugs. The method additionally includes for each of the side effects, building a two-by-two table using the side effect features, and performing a Fisher's exact test using the two-by-two table to determine whether a given one of side effects is differentially shown between positive predicted drug-drug interactions and negative predicted drug-drug interactions.
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公开(公告)号：US10762428B2
公开(公告)日：2020-09-01
申请号：US14966859
申请日：2015-12-11
摘要： A system, method and program product for providing cascade prediction. A system is disclosed having: a computing system for receiving observed cascade data, wherein the observed cascade data includes a set of nodes impacted prior to a preliminary time; a sub-cascade processing engine that determines a sub-cascade size of each node in the set of nodes; survival analysis system that utilizes a networked Weibull regression to determine a survival rate of each node in the set of nodes; and a calculation system that applies the survival rate to the sub-cascade size of each node in the set of nodes to generate a predicted cascade size at a future time.
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公开(公告)号：US10685741B2
公开(公告)日：2020-06-16
申请号：US15289077
申请日：2016-10-07
发明人： Nan Cao , Jianying Hu , Robert K. Sorrentino , Fei Wang , Ping Zhang
摘要： A system and method for analyzing chemical data including a processor and one or more classifiers, stored in memory and coupled to the processor, which further includes an indication predictive module configured to predict whether a given chemical treats a particular indication or not and a side effect predictive module configured to predict whether a given chemical causes a side-effect or not. A correlation engine is configured to determine one or more correlations between one or more indications and one or more side effects for the given chemical and a visualization tool is configured to analyze the one or more correlations and to output results of the analysis.
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公开(公告)号：US10542940B2
公开(公告)日：2020-01-28
申请号：US16149253
申请日：2018-10-02
发明人： Hongfei Li , Buyue Qian , Fei Wang , Xiang Wang
摘要： Electronic health records of a plurality of patients are received. A risk prediction model for a disease based on the electronic health records of the plurality of patients is created. An electronic health record of an original patient is received. A neighboring group of patients of the plurality of patients is identified, wherein the neighboring group of patients is two or more patients similar to the original patient. An ordering of the two or more patients of the neighboring group of patients is received, wherein the ordering of the two or more patients of the neighboring group of patients is based upon how similar each patient of the two or more patients is to the original patient. The risk prediction model is updated based on the ordering of the two or more patients of the neighboring group of patients.
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公开(公告)号：US20190303824A1
公开(公告)日：2019-10-03
申请号：US16442620
申请日：2019-06-17
发明人： Jalal U. Mahmud , Aditya Pal , Fei Wang
摘要： In a method for determining group attributes and matching tasks to a group, a plurality of individual attributes for members of a first group of a plurality of groups are determined, wherein each individual attribute has a type. Parameters of a first distribution of at least one type of individual attribute across members of the first group are estimated. Group attributes of the first group are determined based, at least in part, on the estimated parameters of the first distribution of at least one type of individual attribute. The determined group attributes of the first group are stored in a repository, wherein the repository includes group attributes associated with each group of the plurality of groups. A task is received, wherein the task is associated with a specific group attribute and the task is matched to one group of the plurality of groups based on the specific group attribute.
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公开(公告)号：US10354006B2
公开(公告)日：2019-07-16
申请号：US14922496
申请日：2015-10-26
发明人： Vinod Muthusamy , Wei Tan , Fei Wang , John Erik Wittern
IPC分类号： G06F16/9537 , G06F17/27 , G06F8/10
摘要： A method, system, and recording medium for web Application Programming Interface (API) recommendation, including given a plurality of service description document, gathering a bag of words from the document, generating a service-word matrix based on the bags of words describing the service descriptions, and given a query by a user, recommending a ranked list of services based on the service-word matrix.
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公开(公告)号：US10282460B2
公开(公告)日：2019-05-07
申请号：US15179228
申请日：2016-06-10
发明人： Barton A. Smith , Fei Wang , Wei Zhang , Michelle X. Zhou
摘要： A pairwise relationship data set with multiple attributes (such as, who, what, when, where, how) and with the what attribute (also called the topic attribute) having a word dimension and a people dimension. The data in the topic dimension of the what attribute relates to topics (including other people) relating to the specific, human, personal relationship between the first person and the second person of the pairwise pair. The what attribute data is derived by processing basis data, which includes correspondence data (that is, the substance of correspondence that the first and second persons participate in, including instant messaging and e-mail exchanges. Pairwise relationship data is displayed to a user in real time during a chat session.
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公开(公告)号：US10248699B2
公开(公告)日：2019-04-02
申请号：US15293085
申请日：2016-10-13
发明人： Aditya Pal , Fei Wang
摘要： A computer-implemented method routes a current question to one or more of a plurality of online communities. A computer system can determine, for the current question presented by an asking user a plurality of question-to-question similarity values, a plurality of question-to-user similarity values and a plurality of question-to-community similarity values. The system can select one or more of the plurality of online communities based on the similarity values. The system can route the current question presented by the asking user to the selected one or more of the plurality of online communities.
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公开(公告)号：US20170344710A1
公开(公告)日：2017-11-30
申请号：US15168437
申请日：2016-05-31
发明人： Jianying Hu , Kenney Ng , Adam Perer , Fei Wang , Yajuan Wang
IPC分类号： G06F19/00
摘要： Aspects of the present invention include a method, system and computer program product. The method includes identifying, by a processor, a set of global risk factors for a target event using training patients, and providing, by the processor, a disease progression timeline with defined time stamps by aligning longitudinal data of the training patients based on the defined time stamp of risk targets. The method also includes positioning, by the processor, a target patient at one of the defined time stamps on the disease progression timeline, and identifying, by the processor, at least one of the training patients similar to the target patient with the same one of the defined time stamps on the disease progression timeline. The method further includes calculating, by the processor, a time-varying predictive pattern of at least a portion of the global set of risk factors for the target patient along the disease progression timeline.
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公开(公告)号：US20170242972A1
公开(公告)日：2017-08-24
申请号：US15048413
申请日：2016-02-19
发明人： Jianying Hu , Zhaonan Sun , Fei Wang
IPC分类号： G06F19/00
摘要： An apparatus, method and computer program product for proactive comprehensive generic risk screening. The method performs proactive comprehensive generic risk screening by implementing steps of training comprising steps of receiving cross domain risks and features, optimizing linkage regularization using the received features and the received cross domain risks, said linkage regularization comprising multi-task predictive model training, feature selection and ranking, risk association learning and risk association selection, and outputting patient risk scores, identified high risk patients, risk factors for risks and risk groups, and risk groups and risk associations and calculating risk score for an individual patient comprising steps of receiving individual features comprising patient information, performing said linkage regularization using the received individual features and outputting patient risk scores for said individual patient, and high risk for said individual patient. The calculating risk score can be performed for more than one patient.
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