Method for Assisting Prediction of Risk of Occurence of Side Effect of Irinotecan

    公开(公告)号:US20200172966A1

    公开(公告)日:2020-06-04

    申请号:US16788406

    申请日:2020-02-12

    摘要: An object of the present invention is to provide a simple and efficient device for predicting a risk of occurrence of a side effect of irinotecan by analyzing a single nucleotide polymorphism in a region encoding a specific gene. The prediction of the risk of the occurrence of a side effect of irinotecan is assisted by analyzing a single nucleotide polymorphism in a region encoding the APCDD1L gene, the R3HCC1 gene, the OR5112 gene, the MKKS gene, the EDEM3 gene, or the ACOX1 gene which are present on genomic DNA in a biological sample collected from a test subject; or a single nucleotide polymorphism which is in linkage disequilibrium with or genetically linked to the single nucleotide polymorphism, and determining whether the single nucleotide polymorphism is homozygous for a variant type, heterozygous, or homozygous for a wild-type.

    Information processing device, information processing program, and information processing method

    公开(公告)号:US11461598B2

    公开(公告)日:2022-10-04

    申请号:US16079835

    申请日:2016-12-26

    IPC分类号: G06K9/62 G16H50/20 A61B5/00

    摘要: An information processor can logically support prediction based on past statistical information even though the information contains qualitative or non-numerical data. The processor determines whether an input pattern corresponding to an input object (a determination target) belongs to a specific class among multiple classes, based on feature subsets of any combination of a plurality of features, each feature comprises multiple categories. The processor includes a storage storing the input pattern corresponding to the input object and samples corresponding to respective sample objects and a classification determiner determining whether the input pattern belongs to the specific class. The classification determiner calculates a first conditional probability and a second conditional probability based on the number of the samples belonging to each category of the respective features, the first conditional probability is a probability that the data of the input pattern belong to categories corresponding to the respective feature for the specific class, the second conditional probability is a probability that the data of the input pattern belong to categories corresponding to the respective features for a non-specific class which is a class other than the specific class among classes, and the number of the samples is counted for each class based on the feature information on the samples and the class label information on the samples, and determines whether the input pattern belongs to the specific class based on the feature information on the input pattern, the first conditional probability and the second conditional probability.