A Mixed Model Based Method for Eliminating the Masking Effect of Adverse Drug Reaction

A technology of adverse reactions and mixed models, applied in medical data mining, medical informatics, computer-aided medical procedures, etc., can solve problems such as signal concealment, decision-making influence, false positives, etc., to improve detection performance and weaken data masking effect of influence
CN108538396BActive Publication Date: 2021-08-06NANJING UNIV OF POSTS & TELECOMM
1 Cites 0 Cited by

Patent Information

Authority / Receiving Office
CN Β· China
Patent Type
Patents(China)
Current Assignee / Owner
NANJING UNIV OF POSTS & TELECOMM
Publication Date
2021-08-06

Smart Images

  • Figure 1
    Figure 1
  • Figure 2
    Figure 2
  • Figure 3
    Figure 3
Patent Text Reader

Abstract

The invention discloses a method for eliminating the masking effect of adverse drug reactions based on a mixed model. Based on the report of adverse drug reactions (ADR) in China, firstly, the lasso logistic regression method with the effect of masking and subtraction is used to analyze the ADR database with less correlation The drug-adverse reaction combination is filtered, and the combination with a high degree of correlation is left as the data set after the first round of data screening; secondly, the combination of the number of reports less than or equal to 4 is eliminated by using the removal report method, and the remaining combinations are used as the second screening Finally, the traditional IC algorithm is used to re-detect the signal on the new data set in order to minimize the shadowing effect. The composite reduction model can effectively improve the reduction rate of the shadowing effect, and make the detection of adverse drug reaction signals more reliable and accurate, thereby further ensuring people's drug safety and providing reference for relevant decision-making.
Need to check novelty before this filing date? Find Prior Art

Description

technical field

[0001] The invention relates to the field of signal detection of adverse drug reactions, in particular to a method for eliminating masking effects of adverse drug reactions based on a mixed model. Background technique

[0002] Internationally, the traditional detection methods of Adverse Drug Reaction (ADR) signals are mainly based on the theory of disproportionate determination. Commonly used methods for disproportionation determination theory include PRR, ROR, MHRA, IC, etc. However, due to the large and diverse data in the report, the data of various adverse drug reactions are mixed with each other, and the patients often use combination drugs instead of single drugs, the traditional detection methods of adverse drug reaction signals are often interfered to a certain extent, resulting in many false positives. Positive and false negative results are generated. In addition, due to the large proportion of many routine adverse reactions in the spontaneous re...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More