Supervised machine learning techniques and genetic optimization for occupational diseases risk prediction
Sign Up to like & getrecommendations! Published in 2020 at "Soft Computing"
DOI: 10.1007/s00500-019-04200-2
Abstract: Workers healthcare gained a lot of attention recently as many countries are increasingly concerning about welfare. This paper faces the problem of predicting occupational disease risks by means of computational intelligence and pattern recognition techniques.… read more here.
Keywords: machine; genetic optimization; techniques genetic; learning techniques ... See more keywords
A supervised machine learning-based methodology for analyzing dysregulation in splicing machinery: An application in cancer diagnosis
Sign Up to like & getrecommendations! Published in 2020 at "Artificial intelligence in medicine"
DOI: 10.1016/j.artmed.2020.101950
Abstract: Deregulated splicing machinery components have shown to be associated with the development of several types of cancer and, therefore, the determination of such alterations can help the development of tumor-specific molecular targets for early prognosis… read more here.
Keywords: methodology; machine learning; splicing machinery; supervised machine ... See more keywords
Supervised machine learning for source allocation of per- and polyfluoroalkyl substances (PFAS) in environmental samples.
Sign Up to like & getrecommendations! Published in 2020 at "Chemosphere"
DOI: 10.1016/j.chemosphere.2020.126593
Abstract: Environmental contamination by per- and polyfluoroalkyl substances (PFAS) is widespread, because of both their decades of use, and their persistence in the environment. These factors can make identification of the source of contamination in samples… read more here.
Keywords: source; machine learning; source allocation; supervised machine ... See more keywords
Application of supervised machine learning algorithms in the classification of sagittal gait patterns of cerebral palsy children with spastic diplegia
Sign Up to like & getrecommendations! Published in 2019 at "Computers in biology and medicine"
DOI: 10.1016/j.compbiomed.2019.01.009
Abstract: Gait classification has been widely used for children with cerebral palsy (CP) to assist with clinical decision making and to evaluate different treatment outcomes. The aim of this study was to evaluate supervised machine learning… read more here.
Keywords: classification; machine learning; learning algorithms; supervised machine ... See more keywords
Early prediction of SARS-CoV-2 reproductive number from environmental, atmospheric and mobility data: A supervised machine learning approach
Sign Up to like & getrecommendations! Published in 2022 at "International Journal of Medical Informatics"
DOI: 10.1016/j.ijmedinf.2022.104755
Abstract: Introduction SARS-CoV-2 was declared a pandemic by the WHO on March 11th, 2020. Public protective measures were enforced in every country to limit the diffusion of SARS-CoV-2. Its transmission, mainly by droplets, has been measured… read more here.
Keywords: mobility; number; sars cov; supervised machine ... See more keywords
Prediction of illness remission in patients with Obsessive-Compulsive Disorder with supervised machine learning.
Sign Up to like & getrecommendations! Published in 2021 at "Journal of affective disorders"
DOI: 10.1016/j.jad.2021.09.042
Abstract: INTRODUCTION The course of OCD differs widely among OCD patients, varying from chronic symptoms to full remission. No tools for individual prediction of OCD remission are currently available. This study aimed to develop a machine… read more here.
Keywords: machine learning; remission; predictive performance; supervised machine ... See more keywords
A SEMI-SUPERVISED MACHINE LEARNING PIPELINE FOR CARDIAC RISK STRATIFICATION USING ECHOCARDIOGRAPHIC VARIABLES
Sign Up to like & getrecommendations! Published in 2019 at "Journal of the American College of Cardiology"
DOI: 10.1016/s0735-1097(19)32047-9
Abstract: The current guidelines for echocardiographic assessment of left ventricular diastolic dysfunction (LVDD) utilize decision trees with rigid recursive dichotomizing rules, leading to overlapping and indeterminate outcomes. We investigated a novel machine-learning pipeline to integrate complex… read more here.
Keywords: semi supervised; supervised machine; machine learning; learning pipeline ... See more keywords
Predicting the Ecological Quality Status of Marine Environments from eDNA Metabarcoding Data Using Supervised Machine Learning.
Sign Up to like & getrecommendations! Published in 2017 at "Environmental science & technology"
DOI: 10.1021/acs.est.7b01518
Abstract: Monitoring biodiversity is essential to assess the impacts of increasing anthropogenic activities in marine environments. Traditionally, marine biomonitoring involves the sorting and morphological identification of benthic macro-invertebrates, which is time-consuming and taxonomic-expertise demanding. High-throughput amplicon… read more here.
Keywords: status; edna metabarcoding; marine environments; ecological quality ... See more keywords
Phase behavior of continuous-space systems: A supervised machine learning approach
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Chemical Physics"
DOI: 10.1063/5.0014194
Abstract: The phase behavior of complex fluids is a challenging problem for molecular simulations. Supervised machine learning (ML) methods have shown potential for identifying the phase boundaries of lattice models. In this work, we extend these… read more here.
Keywords: phase; machine learning; supervised machine; phase behavior ... See more keywords
Using supervised machine learning on large-scale online forums to classify course-related Facebook messages in predicting learning achievement within the personal learning environment
Sign Up to like & getrecommendations! Published in 2020 at "Interactive Learning Environments"
DOI: 10.1080/10494820.2018.1515085
Abstract: ABSTRACT This paper demonstrated the use of the supervised Machine Learning (ML) for text classification to predict students’ final course grades in a hybrid Advanced Statistics course and exhibited the potential of using ML classified… read more here.
Keywords: machine learning; learning; online forums; within personal ... See more keywords
Iterative processes: a review of semi-supervised machine learning in rehabilitation science
Sign Up to like & getrecommendations! Published in 2019 at "Disability and Rehabilitation: Assistive Technology"
DOI: 10.1080/17483107.2019.1604831
Abstract: Abstract Purpose: To define semi-supervised machine learning (SSML) and explore current and potential applications of this analytic strategy in rehabilitation research. Method: We conducted a scoping review using PubMed, GoogleScholar and Medline. Studies were included… read more here.
Keywords: machine; machine learning; semi supervised; supervised machine ... See more keywords