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An artificial neural network ensemble approach to generate air pollution maps.

Environmental monitoring and assessment
The objective of this research is to propose an artificial neural network (ANN) ensemble in order to estimate the hourly NO concentration at unsampled locations. Spatial interpolation methods and linear regression models with regularization have been...

EUSKOR: End-to-end coreference resolution system for Basque.

PloS one
This paper describes the process of adapting the Stanford Coreference resolution module to the Basque language, taking into account the characteristics of the language. The module has been integrated in a linguistic analysis pipeline obtaining an end...

Combining mobile-health (mHealth) and artificial intelligence (AI) methods to avoid suicide attempts: the Smartcrises study protocol.

BMC psychiatry
BACKGROUND: The screening of digital footprint for clinical purposes relies on the capacity of wearable technologies to collect data and extract relevant information's for patient management. Artificial intelligence (AI) techniques allow processing o...

Reducing demand uncertainty in the platelet supply chain through artificial neural networks and ARIMA models.

Computers in biology and medicine
One of the significant issues in global healthcare systems is improving the supply chain performance and addressing the uncertainties in demand. Blood products, especially platelets, have the most challenging supply chains in the health system given ...

Machine learning to predict cardiovascular risk.

International journal of clinical practice
AIMS: To analyse the predictive capacity of 15 machine learning methods for estimating cardiovascular risk in a cohort and to compare them with other risk scales.

A comparative study on feature selection for a risk prediction model for colorectal cancer.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Risk prediction models aim at identifying people at higher risk of developing a target disease. Feature selection is particularly important to improve the prediction model performance avoiding overfitting and to identify the...

Qualification of a chemotherapy-compounding robot.

Journal of oncology pharmacy practice : official publication of the International Society of Oncology Pharmacy Practitioners
KIRO® Oncology (Kiro Grifols, Spain) is a robotic system for automated compounding of sterile injectable drugs including intravenous cytotoxic treatments. The present article describes the qualification procedure applied prior to production phases. P...

SALMANTICOR study. Rationale and design of a population-based study to identify structural heart disease abnormalities: a spatial and machine learning analysis.

BMJ open
INTRODUCTION: This study aims to obtain data on the prevalence and incidence of structural heart disease in a population setting and, to analyse and present those data on the application of spatial and machine learning methods that, although known to...

Association between prenatal exposure to multiple persistent organic pollutants (POPs) and growth indicators in newborns.

Environmental research
Despite the fact that many of persistent organic pollutants (POPs) have been banned for decades, they still constitute a group of harmful substances to human health. Prenatal exposure can have adverse effects on one's health as well as on their newbo...