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Computer implementation method and system

A computer and survey data technology, applied in computing, computer-aided medical procedures, computational models, etc., can solve problems such as difficult to present data

Pending Publication Date: 2020-12-25
IQVIA 有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In addition, there may be constraints or other factors that limit access to data from certain providers
Once data is obtained from multiple disparate and heterogeneous sources, it can be difficult to effectively present that data in a user interface, especially if the data obtained will vary on an individual user basis

Method used

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  • Computer implementation method and system
  • Computer implementation method and system
  • Computer implementation method and system

Examples

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Embodiment Construction

[0031] figure 1 An example of a system 100 that can process and / or evaluate clinical trial data using one or more trained models to identify anomalies indicative of adverse events is shown. System 100 includes server 110 , database 120 , and client devices 130 that exchange communications over network 105 . The server 110 also includes a data processing module 112 , a data aggregation module 114 , a data analysis module 116 , a model selector 118 and a prediction module 119 . Database 120 stores survey data 122 , medical record data 124 , and learning models 126 associated with the set of database systems.

[0032] As described throughout, an "adverse event" refers to any event that raises scientific or medical concern for an ongoing clinical trial investigation. For example, according to the Federal Drug Administration (FDA) guidance for clinical trials, an adverse event can mean an event identified during the ongoing surveillance of a medical threatening. Identifying and...

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Abstract

The invention relates to a computer implementation method and system. Aspects of the subject matter described in this specification are embodied in systems and methods that utilize machine-learning techniques to evaluate clinical trial data using one or more learning models trained to identify anomalies representing adverse events associated with a clinical trial investigation. In some implementations, investigation data collected at a clinical trial site is obtained. A set of models corresponding to the clinical trial site is selected. Each model included in the set of models is trained to identify, based on historical investigation data collected at the clinical trial site, a distinct set of one or more indicators that indicate a compliance risk associated with the investigation data. Ascore for the clinical trial site is determined based on the investigation data relative to the historical investigation data. The score represents a likelihood that the investigation data is associated with at least one indicator representing the compliance risk.

Description

technical field [0001] This specification relates to techniques for performing data analysis, and more specifically, for performing predictive analysis. Background technique [0002] Data aggregation can involve compiling data from many different sources. Depending on the nature of the source from which the data being compiled comes, there may be challenges in processing the data to identify patterns in the data. For example, data obtained from disparate data sources may be in different incompatible formats, which requires significant processing power to generate indexes for producing longitudinal mapping. Additionally, there may be constraints or other factors that limit access to data from certain providers. Once data is obtained from multiple disparate and heterogeneous sources, it can be difficult to effectively present that data in a user interface, especially if the data obtained will vary on an individual user basis. Contents of the invention [0003] In general,...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16H10/60G16H15/00G16H10/20G06Q10/06
CPCG16H10/60G16H15/00G16H10/20G06Q10/0635G06Q10/06393G06Q50/18G16H50/70G06N20/20G06N5/01G06N3/045G06N20/00G16H50/20G16H20/10
Inventor V·博纳格里R·帕蒂尔N·塔那维鲁黄建V·P·艾
Owner IQVIA 有限公司