公开(公告)号：US20160342742A1

公开(公告)日：2016-11-24

申请号：US15145222

申请日：2016-05-03

Applicant: SAS Institute Inc.

Inventor： Emily Chapman-McQuiston ,  Diane Emerton ,  Ruth Baldasaro ,  Daniel Kelly

IPC: G06F19/00

CPC classification number: G16H50/70 ,  G16H10/60

Abstract: An apparatus includes a processor and storage to store instructions that cause the processor to identify at least one correlation between a diagnosis group and a medication class for each patient of a first set of patients to derive a set of models for each diagnosis group that correlates the diagnosis group to at least one medication class based on the at least one identified correlation; and for each patient of a second set of patients, employ each model of each set of models to make at least one prediction of at least one diagnosis group as indicated in the corresponding diagnosis group record based on at least one medication class indicated in the corresponding medication class record, and compare the at least one prediction to the corresponding diagnosis group record to derive a tally of at least one of true positives or false positives for each prediction.

Abstract translation: 一种装置包括处理器和存储器，用于存储使得处理器识别第一组患者的每个患者的诊断组与药物类别之间的至少一个相关性的指令，以导出每个诊断组的一组模型， 基于所述至少一个所识别的相关性，诊断组至少一个药物类别; 并且对于第二组患者的每个患者，使用每组模型的每个模型，以基于相应的诊断组记录中指示的至少一个诊断组的至少一个预测，基于相应的 药物分类记录，并且将至少一个预测与相应的诊断组记录进行比较，以得出每个预测的真阳性或假阳性中的至少一个的计数。

公开(公告)号：US09646258B2

公开(公告)日：2017-05-09

申请号：US15274589

申请日：2016-09-23

Applicant: SAS Institute Inc.

Inventor： Steven William Enck ,  Emily Chapman-McQuiston ,  Daniel Kelly

IPC: G06F15/18 ,  G06N7/00 ,  G06F17/30 ,  G06F19/00

CPC classification number: G06N7/005 ,  G06F17/30309 ,  G06F17/30551 ,  G06F17/30961 ,  G06F19/00 ,  G16H50/50

Abstract: Embodiments are generated directed to method, medium, and system including processing circuitry to generate records including randomly selected events for each of one or more subjects having one or more of the same category parameters as a subject of a particular event. The processing circuitry may also present, on a display device, a computer-generated model based on the records, the model having a decision tree data structure having decision tree nodes corresponding with historical events from the records, each of the decision tree nodes having an indication of a likelihood of occurrence for the particular event based on whether a corresponding history event of the decision tree node occurred or did not occur within a specific time period. Embodiments of the real-time distributed nature of the systems and processing discussed herein can solve big data analytics processing problems and facilitate data anomaly detection.

公开(公告)号：US10991466B2

公开(公告)日：2021-04-27

申请号：US15145222

申请日：2016-05-03

Applicant: SAS Institute Inc.

Inventor： Emily Chapman-McQuiston ,  Diane Emerton ,  Ruth Baldasaro ,  Daniel Kelly

IPC: G16H50/70 ,  G16H10/60

Abstract: An apparatus includes a processor and storage to store instructions that cause the processor to identify at least one correlation between a diagnosis group and a medication class for each patient of a first set of patients to derive a set of models for each diagnosis group that correlates the diagnosis group to at least one medication class based on the at least one identified correlation; and for each patient of a second set of patients, employ each model of each set of models to make at least one prediction of at least one diagnosis group as indicated in the corresponding diagnosis group record based on at least one medication class indicated in the corresponding medication class record, and compare the at least one prediction to the corresponding diagnosis group record to derive a tally of at least one of true positives or false positives for each prediction.