Machine learning using convolutional neural networks for SERS analysis of biomarkers in medical diagnostics
Sign Up to like & getrecommendations! Published in 2022 at "Journal of Raman Spectroscopy"
DOI: 10.1002/jrs.6447
Abstract: Abstract Surface‐enhanced Raman spectroscopy (SERS) has wide diagnostic applications because of narrow spectral features that allow multiplexed analysis. Machine learning (ML) has been used for non‐dye‐labeled SERS spectra but has not been applied to SERS… read more here.
Keywords: spectroscopy; machine learning; using convolutional; convolutional neural ... See more keywords
Determining the effects of blended learning using the community of inquiry on nursing students' learning gains in sudden patient deterioration module
Sign Up to like & getrecommendations! Published in 2021 at "Nursing Open"
DOI: 10.1002/nop2.914
Abstract: To determine the effectiveness of blended learning using the community of inquiry framework on nursing students' learning gains in a sudden patient deterioration module. read more here.
Keywords: nursing students; blended learning; using community; students learning ... See more keywords
CellOrganizer: Learning and Using Cell Geometries for Spatial Cell Simulations.
Sign Up to like & getrecommendations! Published in 2019 at "Methods in molecular biology"
DOI: 10.1007/978-1-4939-9102-0_11
Abstract: This chapter describes the procedures necessary to create generative models of the spatial organization of cells directly from microscope images and use them to automatically provide geometries for spatial simulations of cell processes and behaviors.… read more here.
Keywords: cellorganizer learning; geometries spatial; learning using; using cell ... See more keywords
Bayesian network hybrid learning using an elite-guided genetic algorithm
Sign Up to like & getrecommendations! Published in 2018 at "Artificial Intelligence Review"
DOI: 10.1007/s10462-018-9615-5
Abstract: Bayesian networks (BNs) constitute a powerful framework for probabilistic reasoning and have been extensively used in different research domains. This paper presents an improved hybrid learning strategy that features parameterized genetic algorithms (GAs) to learn… read more here.
Keywords: using elite; elite guided; bayesian network; hybrid learning ... See more keywords
Computer-assisted learning using the Cabri 3D for improving spatial ability and self- regulated learning
Sign Up to like & getrecommendations! Published in 2020 at "Heliyon"
DOI: 10.1016/j.heliyon.2020.e05536
Abstract: Spatial ability and self-regulated learning have broad implications for students. Therefore, this study aimed to determine the improvement of spatial ability and self-regulated learning of students who obtain computer-assisted learning using the 3D Cabri program.… read more here.
Keywords: class; regulated learning; spatial ability; learning using ... See more keywords
Pain phenotypes classified by machine learning using electroencephalography features
Sign Up to like & getrecommendations! Published in 2020 at "NeuroImage"
DOI: 10.1016/j.neuroimage.2020.117256
Abstract: Pain is a multidimensional experience mediated by distributed neural networks in the brain. To study this phenomenon, EEGs were collected from 20 subjects with chronic lumbar radiculopathy, 20 age and gender matched healthy subjects, and… read more here.
Keywords: machine; machine learning; pain phenotypes; classified machine ... See more keywords
Personalized Policy Learning Using Longitudinal Mobile Health Data
Sign Up to like & getrecommendations! Published in 2021 at "Journal of the American Statistical Association"
DOI: 10.1080/01621459.2020.1785476
Abstract: Abstract Personalized policy represents a paradigm shift one decision rule for all users to an individualized decision rule for each user. Developing personalized policy in mobile health applications imposes challenges. First, for lack of adherence,… read more here.
Keywords: policy learning; policy; personalized policy; mobile health ... See more keywords
Learning, using and exchanging global competence in the context of international postgraduate mobility
Sign Up to like & getrecommendations! Published in 2018 at "Globalisation, Societies and Education"
DOI: 10.1080/14767724.2017.1387768
Abstract: ABSTRACT The paper offers a theoretically grounded analysis of international postgraduate students’ perspectives on the importance and development of global citizenship knowledge and competences while they are studying, and how these are valued and enacted… read more here.
Keywords: international postgraduate; mobility; postgraduate; using exchanging ... See more keywords
Confused or not: decoding brain activity and recognizing confusion in reasoning learning using EEG
Sign Up to like & getrecommendations! Published in 2023 at "Journal of Neural Engineering"
DOI: 10.1088/1741-2552/acbfe0
Abstract: Objective. Confusion is the primary epistemic emotion in the learning process, influencing students’ engagement and whether they become frustrated or bored. However, research on confusion in learning is still in its early stages, and there… read more here.
Keywords: reasoning learning; confusion reasoning; using eeg; confusion ... See more keywords
Using sociocultural insights to enhance work-integrated learning
Sign Up to like & getrecommendations! Published in 2018 at "Higher Education, Skills and Work-based Learning"
DOI: 10.1108/heswbl-09-2017-0071
Abstract: When learning in the workplace is conceptualised as a social process, different social or cultural features of workplaces may enable or constrain students’ learning. The purpose of this paper is to understand the views of… read more here.
Keywords: work; work integrated; integrated learning; wil experiences ... See more keywords
Ensemble Learning Using Individual Neonatal Data for Seizure Detection
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Journal of Translational Engineering in Health and Medicine"
DOI: 10.1109/jtehm.2022.3201167
Abstract: Objective: Sharing medical data between institutions is difficult in practice due to data protection laws and official procedures within institutions. Therefore, most existing algorithms are trained on relatively small electroencephalogram (EEG) data sets which is… read more here.
Keywords: neonatal data; ensemble learning; data seizure; individual neonatal ... See more keywords