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Found 8 papers, 0 papers with code
An End-to-End Deep Learning Histochemical Scoring System for Breast Cancer Tissue Microarray
To the best of our knowledge, this is the first end-to-end system that takes a TMA image as input and directly outputs a clinical score.
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.
Signalling Paediatric Side Effects using an Ensemble of Simple Study Designs
Conclusion: This research shows that it is possible to exploit the mechanism of causality and presents a framework for signalling adverse drug reactions effectively.
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.
Biomarker Clustering of Colorectal Cancer Data to Complement Clinical Classification
In this paper, we describe a dataset relating to cellular and physical conditions of patients who are operated upon to remove colorectal tumours.
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.
