Search results for "informatics"

Activación plaquetaria e hipercolesterolemia en la patogenia de la trombosis venosa profunda

2006

Currently it is accepted that deep vein thrombosis is a multifactorial event in which the presence of activated platelets and also plasmatic lipids seems to play a pivotal role that it is not well established in the scientific bibliography. Due to the non consensus state about these topics between the different groups working in these aspects, the topic involving deep vein thrombosis-platelets-lipids, and also their interactions, still is an interesting area of investigation, in which it is necessary to carry out studies with the aim of establishing risk factors, initial diagnostic methods and clinical assays to probe the efficacy of new therapies.

2021

Abstract Reliable patient-specific ventricular repolarization times (RTs) can identify regions of functional block or afterdepolarizations, indicating arrhythmogenic cardiac tissue and the risk of sudden cardiac death. Unipolar electrograms (UEs) record electric potentials, and the Wyatt method has been shown to be accurate for estimating RT from a UE. High-pass filtering is an important step in processing UEs, however, it is known to distort the T-wave phase of the UE, which may compromise the accuracy of the Wyatt method. The aim of this study was to examine the effects of high-pass filtering, and improve RT estimates derived from filtered UEs. We first generated a comprehensive set of UE…

Global prevalence and genotype distribution of hepatitis C virus infection in 2015:a modelling study

2017

WOS: 000426979400014

Convolutional architectures for virtual screening

2020

Abstract Background A Virtual Screening algorithm has to adapt to the different stages of this process. Early screening needs to ensure that all bioactive compounds are ranked in the first positions despite of the number of false positives, while a second screening round is aimed at increasing the prediction accuracy. Results A novel CNN architecture is presented to this aim, which predicts bioactivity of candidate compounds on CDK1 using a combination of molecular fingerprints as their vector representation, and has been trained suitably to achieve good results as regards both enrichment factor and accuracy in different screening modes (98.55% accuracy in active-only selection, and 98.88% …

In Silico Prediction of Caco-2 Cell Permeability by a Classification QSAR Approach

2011

In the present study, 21 validated QSAR models that discriminate compounds with high Caco-2 permeability (Papp ≥8×10(-6)  cm/s) from those with moderate-poor permeability (Papp <8×10(-6)  cm/s) were developed on a novel large dataset of 674 compounds. 20 DRAGON descriptor families were used. The global accuracies of obtained models were ranking between 78-82 %. A general model combining all types of molecular descriptors was developed and it classified correctly 81.56 % and 83.94 % for training and test sets, respectively. An external set of 10 compounds was predicted and 80 % was correctly assessed by in vitro Caco-2 assays. The potential use of the final model was evaluated by a virtual s…

Visceral Adiposity Index: An Indicator of Adipose Tissue Dysfunction

2013

The Visceral Adiposity Index (VAI) has recently proven to be an indicator of adipose distribution and function that indirectly expresses cardiometabolic risk. In addition, VAI has been proposed as a useful tool for early detection of a condition of cardiometabolic risk before it develops into an overt metabolic syndrome. The application of the VAI in particular populations of patients (women with polycystic ovary syndrome, patients with acromegaly, patients with NAFLD/NASH, patients with HCV hepatitis, patients with type 2 diabetes, and general population) has produced interesting results, which have led to the hypothesis that the VAI could be considered a marker of adipose tissue dysfuncti…

Effects of different lower-limb sensory stimulation strategies on postural regulation-a Systematic review and metaanalysis

2017

Systematic reviews of balance control have tended to only focus on the effects of single lower-limb stimulation strategies, and a current limitation is the lack of comparison between different relevant stimulation strategies. The aim of this systematic review and meta-analysis was to examine evidence of effects of different lower-limb sensory stimulation strategies on postural regulation and stability. Moderate- to high-pooled effect sizes (Unbiased (Hedges' g) standardized mean differences (SMD) = 0.31-0.66) were observed with the addition of noise in a Stochastic Resonance Stimulation Strategy (SRSS), in three populations (i.e., healthy young adults, older adults, and individuals with low…

Multivariate EEG spectral analysis evidences the functional link between motor and visual cortex during integrative sensorimotor tasks

2012

The identification of the networks connecting brain areas and the understanding of their role in executing complex tasks is a crucial issue in cognitive neuroscience. In this study, specific visuomotor tasks were devised to reveal the functional network underlying the cooperation process between visual and motor regions. Electroencephalography (EEG) data were recorded from twelve healthy subjects during a combined visuomotor task, which integrated precise grip motor commands with sensory visual feedback (VM). This condition was compared with control tasks involving pure motor action (M), pure visual perception (V) and visuomotor performance without feedback (V + M). Multivariate parametric …

Classification of diabetes-related retinal diseases using a deep learning approach in optical coherence tomography

2019

Background and objectives: Spectral Domain Optical Coherence Tomography (SD-OCT) is a volumetric imaging technique that allows measuring patterns between layers such as small amounts of fluid. Since 2012, automatic medical image analysis performance has steadily increased through the use of deep learning models that automatically learn relevant features for specific tasks, instead of designing visual features manually. Nevertheless, providing insights and interpretation of the predictions made by the model is still a challenge. This paper describes a deep learning model able to detect medically interpretable information in relevant images from a volume to classify diabetes-related retinal d…

Digitalisation of municipal healthcare collaboration with volunteers: a case study applying normalization process theory

2021

Abstract Background Increasing use of volunteers in healthcare requires structured collaboration between healthcare services and volunteers. The aim of this research was to explore critical issues and strategies in the implementation process of a digital solution for collaboration with and coordination of volunteers in municipal healthcare services. Methods Qualitative data collection was used to study implementation of a digital system for collaboration with volunteers in three Norwegian municipalities. Three rounds of interviews were conducted with healthcare employees from a volunteer centre and from municipality healthcare units in three municipalities: before implementation, and 6 and …