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BACKGROUND Endoscopic mucosal resection (EMR) is currently the most used technique for resection of large distal colorectal polyps. However, in large lesions EMR can often only be performed in a piecemeal fashion resulting in relatively low radical (R0)-resection rates and high recurrence rates. Endoscopic submucosal dissection (ESD) is a newer procedure(More)
INTRODUCTION Severity of mucosal inflammation is shown to be associated with Barrett's esophagus (BE) development in animals. It has therefore been postulated that a strong pro-inflammatory host response predisposes to BE. AIM To determine the impact of cytokine gene polymorphisms on the development of BE. METHODS The multiplex SNaPshot method was used(More)
BACKGROUND The continuous exposure of esophageal epithelium to refluxate may induce ectopic expression of bile-responsive genes and contribute to the development of Barrett's esophagus (BE) and esophageal adenocarcinoma. In normal physiology of the gut and liver, the nuclear receptor Pregnane × Receptor (PXR) is an important factor in the detoxification of(More)
OBJECTIVE Machine learning techniques can be used to extract predictive models for diseases from electronic medical records (EMRs). However, the nature of EMRs makes it difficult to apply off-the-shelf machine learning techniques while still exploiting the rich content of the EMRs. In this paper, we explore the usage of a range of natural language(More)
BACKGROUND Second primary malignancies are a major cause of excess morbidity and mortality in cancer survivors. Hodgkin lymphoma survivors who were treated with infradiaphragmatic radiotherapy and/or high-dose procarbazine have an increased risk to develop colorectal cancer. Colonoscopy surveillance plays an important role in colorectal cancer prevention by(More)
Over the past years, research utilizing routine care data extracted from Electronic Medical Records (EMRs) has increased tremendously. Yet there are no straightforward, standardized strategies for pre-processing these data. We propose a dedicated medical pre-processing pipeline aimed at taking on many problems and opportunities contained within EMR data,(More)
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