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Found 9 papers, 0 papers with code
Identifying Candidate Risk Factors for Prescription Drug Side Effects using Causal Contrast Set Mining
Big longitudinal observational databases present the opportunity to extract new knowledge in a cost effective manner.
Personalising Mobile Advertising Based on Users Installed Apps
The results showed there were clear differences in the way the profiles interact with the different advert genres and the results of this paper suggest that mobile advert targeting would improve the frequency that users interact with an advert.
Attributes for Causal Inference in Longitudinal Observational Databases
In this paper we investigate potential attributes that can be used in causal inference to identify side effects based on the Bradford-Hill causality criteria.
A Novel Semi-Supervised Algorithm for Rare Prescription Side Effect Discovery
Drugs are frequently prescribed to patients with the aim of improving each patient's medical state, but an unfortunate consequence of most prescription drugs is the occurrence of undesirable side effects.
Comparison of algorithms that detect drug side effects using electronic healthcare databases
In this paper we apply four existing electronic healthcare database signal detecting algorithms (MUTARA, HUNT, Temporal Pattern Discovery and modified ROR) on the THIN database for a selection of drugs from six chosen drug families.
Comparing Data-mining Algorithms Developed for Longitudinal Observational Databases
Longitudinal observational databases have become a recent interest in the post marketing drug surveillance community due to their ability of presenting a new perspective for detecting negative side effects.
Discovering Sequential Patterns in a UK General Practice Database
The wealth of computerised medical information becoming readily available presents the opportunity to examine patterns of illnesses, therapies and responses.
Quiet in Class: Classification, Noise and the Dendritic Cell Algorithm
It is found that this feature, while advantageous for noisy, time-ordered classification, is not as useful as a traditional static filter for processing a synthetic dataset.
Investigating the Detection of Adverse Drug Events in a UK General Practice Electronic Health-Care Database
In this paper, existing methods developed for spontaneous reporting databases are implemented on both a spontaneous reporting database and a general practice electronic health-care database and compared.
