Sentence examples for generating a disease from inspiring English sources

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The study could only be run in practices that had a practice nurse on staff to carry out the intervention and had access to clinical software capable of generating a disease registry from which patients could be selected to participate in the trial.

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We reasoned that the generation of the SJIA urine biomarker peptides, including those derived from fibrinogen, may be an outcome of the actions of inflammatory mediators on protease expression and regulation, generating a disease-specific degradation pattern of source proteins, such as fibrinogen.

With this disease model, we randomly generated a disease population with 10,000 affected individuals and a general population with 10,000 unaffected individuals from the population of 500,000 individuals.

We generated a disease network which consists of 591 diseases and 6,931 disease relationships.

We generated a disease network (DN) which consists of 591 nodes (diseases) and 6,931 edges (disease relationships) based on a default E score cutoff (Materials & Methods).

First, we generate a disease list from 15 ranked sources, using disease-name unification heuristics.

To further visualize how the clinical parameters are interconnected we generated a disease network tool showing the association between diseases.

Specialists with expertise in palliative care and interstitial lung disease, who were part of the research team, generated a disease typology to classify patients into four stages of IPF described in Table  2.

We were able to run TrueBlue only in practices that used clinical software, which we used to generate a disease registry from which participants could be selected, and had a PN on staff.

Introduction of the Scn8a N1768D mutation into the mouse genome has generated a disease model that reproduces several key aspects of the human disorder, including generalized seizures, epileptiform events on EEG, impaired motor coordination and SUDEP, confirming the causal role of the de novo SCN8A mutation in these aspects of the disorder.

A combination of large-scale in-house sequencing, gene expression profiling and public sequence and gene expression data mining were used to characterise the transcriptome of NSCLC and the data used to generate a disease-focused microarray – the Lung Cancer DSA research tool.

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