Irritable Bowel Syndrome (IBS) is a functional bowel disorder characterized by abdominal pain or discomfort and altered bowel habits in absence of Amiami detectable structural abnormalities with worldwide incidence of 10-20%.According to Rome IV criteria subtypes of IBS can be IBS-D, IBS-C and IBS-M.Both non pharmacological and pharmacological ther
RBF-MLMR: A Multi-Label Metamorphic Relation Prediction Approach Using RBF Neural Network
Metamorphic testing has been successfully MUSTARD used in many different fields to solve the test oracle problem.However, how to find a set of appropriate metamorphic relations for metamorphic testing remains a complicated and tedious task.Recently some machine learning approaches have been proposed to predict metamorphic relations.These approaches
Multivariate models based on infrared spectra as a substitute for oil property correlations to predict thermodynamic properties: evaluated on the basis of the narrow-boiling fractions of Kukersite retort oil
This article investigates a potential for using models based on infrared spectra to predict basic thermodynamic properties of narrow boiling range oil fractions or pseudocomponents.The work took advantage of the simultaneous availability of a property database of narrow boiling range fractions of Kukersite oil shale retort RAPID MASS CREAMY VANILLA
Machine learning algorithm for early-stage prediction of severe morbidity in COVID-19 pneumonia patients based on bio-signals
Abstract Background Paralysis of medical systems has emerged as a major problem not only in Korea but also globally because of the COVID-19 pandemic.Therefore, early identification and treatment of COVID-19 are crucial.This study aims to develop a machine-learning algorithm based on bio-signals that predicts the infection three days in advance befo