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OBJECTIVE To investigate the association between fish and seafood intake and new-onset type 2 diabetes. RESEARCH DESIGN AND METHODS This was a population-based prospective cohort (European Prospective Investigation of Cancer [EPIC]-Norfolk) study of men and women aged 40-79 years at baseline (1993-1997). Habitual fish and seafood intake (white fish, oily(More)
BACKGROUND Epidemiologic evidence of an association between fish intake and type 2 diabetes (T2D) is inconsistent and unresolved. OBJECTIVE The objective was to examine the association between total and type of fish intake and T2D in 8 European countries. DESIGN This was a case-cohort study, nested within the European Prospective Investigation into(More)
OBJECTIVE The evidence on the association between fish consumption, dietary long-chain n-3 fatty acids, and risk of type 2 diabetes is inconsistent. We therefore performed a systematic review and meta-analysis of the available prospective evidence. RESEARCH DESIGN AND METHODS Studies were identified by searching the PubMed and EMBASE databases through 15(More)
A fully automated, high-throughput method was developed to profile the fatty acids of phospholipids from human plasma samples for application to a large epidemiological sample set (n > 25,000). We report here on the data obtained for the quality-control materials used with the first 860 batches, and the validation process used. The method consists of two(More)
BACKGROUND Stable-isotope ratios of carbon (¹³C/¹²C, expressed as δ¹³C) and nitrogen (¹⁵N/¹⁴N, or δ¹⁵N) have been proposed as potential nutritional biomarkers to distinguish between meat, fish, and plant-based foods. OBJECTIVE The objective was to investigate dietary correlates of δ¹³C and δ¹⁵N and examine the association of these biomarkers with incident(More)
This paper describes the approach used by ezDI at the SemEval 2015 Task-14: " Analysis of Clinical Text ". The task was divided into two embedded tasks. Task-1 required determining disorder boundaries (including the discontiguous ones) from a given set of clinical notes and normalizing the disorders by assigning a unique CUI from the UMLS/SNOMEDCT 1. Task-2(More)
This paper describes the system used in Task-7 (Analysis of Clinical Text) of SemEval-2014 for detecting disorder mentions and associating them with their related CUI of UMLS 1. For Task-A, a CRF based sequencing algorithm was used to find different medical entities and a binary SVM classifier was used to find relationship between entities. For Task-B, a(More)
This work is licenced under a Creative Commons Attribution 4.0 International License. Page numbers and proceedings footer are added by the organizers. License details: Abstract [We report of the procedures of developing a large representative corpus of 50,000 sentences taken from clinical notes. Previous reports of annotated corpus of clinical notes have(More)
A clinical document contains vital information about patient's healthcare in unstructured free text format, so Information Extraction and Named Entity Recognition are essential to extract meaningful information from this free clinical text. Here we propose a CRF-based supervised learning approach using customized clinical features set to recognize named(More)