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公开(公告)号：US10783997B2
公开(公告)日：2020-09-22
申请号：US15248734
申请日：2016-08-26
发明人： Achille B. Fokoue-Nkoutche , Oktie Hassanzadeh , Mohammad S. Hamedani , Meinolf Sellmann , Ping Zhang
摘要： Embodiments include method, systems and computer program products for predicting adverse drug events on a computational system. Aspects include receiving a personalized data set including a plurality of real-time drug doses for a first drug or drug combination and a plurality of corresponding real-time adverse drug reaction tolerance data for the first drug or drug combination for a patient. Aspects also include receiving known drug data for a candidate drug or drug pair. Aspects also include calculating, based upon the known drug data and the personalized data set, a predicted adverse drug reaction tolerance for the candidate drug or drug pair at a candidate dosage, wherein the predicted adverse drug reaction tolerance is personalized to the patient.
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公开(公告)号：US09785673B2
公开(公告)日：2017-10-10
申请号：US15196237
申请日：2016-06-29
发明人： Mihaela A. Bornea , Julian Dolby , Achille B. Fokoue-Nkoutche , Anastasios Kementsietsidis , Kavitha Srinivas
CPC分类号： G06F17/30469 , G06F17/30442 , G06F17/30477 , G06F17/3053 , G06F17/30935 , G06F17/30958
摘要： Systems and methods for optimizing a query, and more particularly, systems and methods for finding optimal plans for graph queries by casting the task of finding the optimal plan as an integer programming (ILP) problem. A method for optimizing a query, comprises building a data structure for a query, the data structure including a plurality of components, wherein each of the plurality of components corresponds to at least one graph pattern, determining a plurality of flows of query variables between the plurality of components, and determining a combination of the plurality of flows between the plurality of components that results in a minimum cost to execute the query.
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公开(公告)号：US10902943B2
公开(公告)日：2021-01-26
申请号：US15982281
申请日：2018-05-17
摘要： Embodiments of the present invention disclose a method, a computer program product, and a computer system for predicting drug and food interactions. A computer identifies one or more drug similarity measures between one or more drugs and one or more food similarity measures between one or more foods. In addition, the computer identifies one or more interactions between the one or more drugs and the one or more foods, then calculates one or more drug-food feature vectors based on the one or more interactions, the one or more drug similarity measures, and the one or more food similarity measures. Furthermore, the computer calculates a first probability indicating whether a first drug of the one or more drugs will interact with a first food of the one or more foods based on a model, wherein the model is trained based on the one or more drug-food feature vectors.
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公开(公告)号：US20190355458A1
公开(公告)日：2019-11-21
申请号：US15982281
申请日：2018-05-17
摘要： Embodiments of the present invention disclose a method, a computer program product, and a computer system for predicting drug and food interactions. A computer identifies one or more drug similarity measures between one or more drugs and one or more food similarity measures between one or more foods. In addition, the computer identifies one or more interactions between the one or more drugs and the one or more foods, then calculates one or more drug-food feature vectors based on the one or more interactions, the one or more drug similarity measures, and the one or more food similarity measures. Furthermore, the computer calculates a first probability indicating whether a first drug of the one or more drugs will interact with a first food of the one or more foods based on a model, wherein the model is trained based on the one or more drug-food feature vectors.
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公开(公告)号：US20190332964A1
公开(公告)日：2019-10-31
申请号：US15966096
申请日：2018-04-30
摘要： A method, computer system, and a computer program product for determining a composite similarity metric for data of a first data type is provided. The present invention may include providing a plurality of similarity metrics for the first data type. The present invention may also include providing a metric quantifying correlation of entities belonging to the first data type and entities belonging to a second data type. The present invention may then include developing a first regression model to predict values of the provided metric quantifying correlation of entities belonging to the first data type and entities belonging to the second data type using the provided plurality of similarity metrics. The present invention may further include calculating the composite similarity metric from a plurality of first regression coefficients in the developed first regression model.
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公开(公告)号：US20170116376A1
公开(公告)日：2017-04-27
申请号：US14920327
申请日：2015-10-22
发明人： Achille B. Fokoue-Nkoutche , Oktie Hassanzadeh , Mohammad Sadoghi Hamedani , Meinolf Sellmann , Ping Zhang
IPC分类号： G06F19/00
CPC分类号： G06F19/326 , G06F19/3456
摘要： Embodiments include method, systems and computer program products for predicting adverse drug events on a computational system. Aspects include receiving known drug data from drug databases and one or more of a candidate drug, a drug pair, and a candidate drug-patient pair. Aspects also include calculating an adverse event prediction rating representing a confidence level of an adverse drug event for the candidate drug, a drug pair, and a candidate drug-patient pair, the rating being based on the known drug data. Aspects also include associating adverse event features with the candidate drug, drug pair, or a candidate drug-patient pair, including a nature, cause, mechanism, or severity of the adverse drug event. Aspects also include calculating and outputting an adverse event prediction rating.
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公开(公告)号：US20160154849A1
公开(公告)日：2016-06-02
申请号：US14993272
申请日：2016-01-12
发明人： Mihaela A. Bornea , Julian Dolby , Achille B. Fokoue-Nkoutche , Anastasios Kementsietsidis , Kavitha Srinivas
IPC分类号： G06F17/30
CPC分类号： G06F17/30469 , G06F17/30442 , G06F17/30477 , G06F17/3053 , G06F17/30935 , G06F17/30958
摘要： Systems and methods for optimizing a query, and more particularly, systems and methods for finding optimal plans for graph queries by casting the task of finding the optimal plan as an integer programming (ILP) problem. A method for optimizing a query, comprises building a data structure for a query, the data structure including a plurality of components, wherein each of the plurality of components corresponds to at least one graph pattern, determining a plurality of flows of query variables between the plurality of components, and determining a combination of the plurality of flows between the plurality of components that results in a minimum cost to execute the query.
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公开(公告)号：US11354591B2
公开(公告)日：2022-06-07
申请号：US16157660
申请日：2018-10-11
摘要： Mechanisms are provided to implement a genomic database curation (GDC) system. The GDC system generates a ground truth database based on a training subset of datasets from an uncurated large scale genomic database, and label metadata for the training subset. The GDC system trains at least one classification engine of the GDC system based on the training subset and the ground truth database at least by performing a machine learning operation on the at least one classification engine. The GDC system automatically applies the at least one trained classification engine on the uncurated large scale genomic database to generate an automatically curated large scale genomic database. A meta-classifier engine generates an output specifying at least one of significant gene signatures or gene pathways for at least one of diseases or drug agents based on the automatically curated large scale genomic database.
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公开(公告)号：US20190333645A1
公开(公告)日：2019-10-31
申请号：US15966064
申请日：2018-04-30
IPC分类号： G16H50/80
摘要： A method, computer system, and a computer program product for analyzing data belonging to a plurality of data types wherein data belonging to a first data type of the plurality of data types may be correlated with data belonging to a second data type of the plurality of data types is provided. The present invention may include providing at least one first metric quantifying similarity of entities belonging to the first data type. The present invention may then include providing a second metric quantifying correlation of entities belonging to the first data type and entities belonging to the second data type. The present invention may also include inferring a value of the second metric correlating a first entity of the first data type with a second entity of the second data type.
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公开(公告)号：US20190303535A1
公开(公告)日：2019-10-03
申请号：US15943773
申请日：2018-04-03
发明人： Achille B. Fokoue-Nkoutche , YINGKAI Gao , HENG LUO , PING ZHANG , Sanjoy Dey
摘要： Link prediction for biomedical entities. A neural network is trained using known associations between biomedical entities, including their vector representations and additional information-carrying content describing the biomedical entities. The trained network infers or predicts unobserved associations between two entities.
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