QUERY OPTIMIZER FOR COMBINED STRUCTURED AND UNSTRUCTURED DATA RECORDS
    2.
    发明申请
    QUERY OPTIMIZER FOR COMBINED STRUCTURED AND UNSTRUCTURED DATA RECORDS 审中-公开
    用于组合结构化和非结构化数据记录的查询优化器

    公开(公告)号:WO2017180475A1

    公开(公告)日:2017-10-19

    申请号:PCT/US2017/026636

    申请日:2017-04-07

    Abstract: A method of optimizing a query over a database, the method includes obtaining a set of data records from the database, the data records containing structured data and unstructured data documents, extracting the structured and unstructured data from the set of data records, transforming the structured and unstructured data into a vector that is an element of a weighted vector space, receiving a target data record containing structured and unstructured data, generating a target vector for the target data record, executing a similarity algorithm using the target vector and the weighted vector space generated by the collection of database records to provide a reduced number of data records that are most similar to the target data record, and executing a query against the reduced number of data records that are most similar to the target data record.

    Abstract translation: 一种优化对数据库的查询的方法,所述方法包括从数据库获得一组数据记录,所述数据记录包含结构化数据和非结构化数据文档,从所述数据库中提取结构化和非结构化数据 将结构化和非结构化数据变换成作为加权矢量空间的元素的矢量,接收包含结构化和非结构化数据的目标数据记录,生成目标数据记录的目标矢量,使用相似度算法 目标向量和由数据库记录集合生成的加权向量空间,以提供与目标数据记录最相似的数据记录的数量减少,以及针对减少数量的数据记录执行查询,该数据记录与 目标数据记录。

    MACHINE LEARNING QUANTIFICATION OF TARGET ORGANISMS USING NUCLEIC ACID AMPLIFICATION ASSAYS

    公开(公告)号:WO2020170051A1

    公开(公告)日:2020-08-27

    申请号:PCT/IB2020/050607

    申请日:2020-01-27

    Abstract: In some examples, a system for amplifying and quantifying a target organism present in a sample includes a detection device configured to amplify and detect a nucleic acid associated with the target organism. The detection device configured to receive a sample and to amplify nucleic acid in the sample over an amplification cycle. The detection device is configured to capture a data set including measurements of the nucleic acid collected during the amplification cycle. The system further includes a computing device configured to receive the data set and to apply a machine learning system to the data set. The machine learning system is trained to estimate a quantity of the target organism present in the sample based on the measurements in the data set.

    MEDICAL PROTOCOL EVALUATION
    6.
    发明申请
    MEDICAL PROTOCOL EVALUATION 审中-公开
    医疗方案评估

    公开(公告)号:WO2017079012A1

    公开(公告)日:2017-05-11

    申请号:PCT/US2016/058980

    申请日:2016-10-27

    CPC classification number: G06Q50/22 G06F19/00

    Abstract: A computer-implemented method of evaluating a plurality of protocols associated with a medical context includes receiving, with a computer system, an indication of a medical context item corresponding to a medical context, accessing, with the computer system, a digital library including a plurality of protocols associated with the medical context, assigning, with the computer system, predictive outcomes to one or more of plurality of protocols, selecting, with the computer system, one of the plurality of protocols associated with the medical context based upon the assigned predictive outcomes, and storing, with the computer system within a database, an indication the selected protocol is assigned to the medical context item.

    Abstract translation: 用于评估与医学背景相关联的多个协议的计算机实现的方法包括利用计算机系统接收对应于医学背景的医学背景项目的指示,利用计算机 系统,数字图书馆,所述数字图书馆包括与所述医学背景相关联的多个协议;与所述计算机系统一起为多个协议中的一个或多个分配预测结果;利用所述计算机系统选择与所述多个协议 基于所分配的预测结果的医疗背景,并且将计算机系统存储在数据库内,将所选协议分配给医疗背景项目的指示。

    IDENTIFICATION OF LOW-EFFICACY PATIENT POPULATION
    8.
    发明申请
    IDENTIFICATION OF LOW-EFFICACY PATIENT POPULATION 审中-公开
    低效患者人群的识别

    公开(公告)号:WO2017079047A1

    公开(公告)日:2017-05-11

    申请号:PCT/US2016/059315

    申请日:2016-10-28

    CPC classification number: G06Q50/22 G06F19/00 G06Q10/10

    Abstract: A method of evaluating a plurality of patient protocols associated with a medical context, the method including, with a computer system, accessing a database including medical information for a plurality of patients associated with the medical context items. For each of the patients, the medical information includes an indication that one of the patient protocols is associated with the patient. The method further includes, with the computer system, evaluating each of the patient protocols based on medical information associated with patients within a patient population, the patient population representing a subset of the patients, to estimate an efficacy of each of the patient protocols for the patient population, and identifying the patient population represents a low-efficacy patient population based on the efficacy estimates for the patient population. The method further includes storing, within the database, an indication that the patient population represents the low-efficacy patient population.

    Abstract translation: 一种评估与医学背景相关联的多个患者协议的方法,所述方法包括利用计算机系统访问数据库,所述数据库包括与所述医学背景项目相关联的多个患者的医疗信息。 对于每个患者,医疗信息包括患者协议之一与患者相关的指示。 该方法还包括利用计算机系统基于与患者群体内的患者相关联的医疗信息来评估每个患者方案,患者群体代表患者的子集,以估计每个患者方案对于 患者人群和鉴定患者群体代表基于患者群体的功效估计的低效率患者群体。 该方法还包括在数据库内存储患者群代表低效率患者群的指示。

    SYSTEM AND METHOD FOR DETECTING INHIBITION OF A BIOLOGICAL ASSAY

    公开(公告)号:WO2020234718A1

    公开(公告)日:2020-11-26

    申请号:PCT/IB2020/054617

    申请日:2020-05-15

    Abstract: In some examples, a system for detecting inhibition of a biological assay includes a detection device configured to amplify and detect a target nucleic acid. The detection device is configured to receive a sample comprising a matrix and a quantity of the target nucleic acid and to amplify the target nucleic acid within the sample over a nucleic acid amplification cycle. The detection device is configured to capture a data set including measurements of the nucleic acid collected during the amplification cycle. The system further includes a computing device configured to receive the data set and to apply a machine-learning system to the data set to detect inhibited biological assays that tested negative for the target nucleic acid due to matrix inhibition.

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