Usability guideline for Mobile learning applications: an update
Sign Up to like & getrecommendations! Published in 2019 at "Education and Information Technologies"
DOI: 10.1007/s10639-019-09937-9
Abstract: Mobile learning application developers have to overcome inherent limitations imposed by mobile devices in order to produce usable applications. There are usability guidelines available to assist in the design process but with technological improvements, these… read more here.
Keywords: learning applications; mobile learning; usability guideline; usability ... See more keywords
Using HPC infrastructures for deep learning applications in fusion research
Sign Up to like & getrecommendations! Published in 2021 at "Plasma Physics and Controlled Fusion"
DOI: 10.1088/1361-6587/ac0a3b
Abstract: In the fusion community, the use of high performance computing (HPC) has been mostly dominated by heavy-duty plasma simulations, such as those based on particle-in-cell and gyrokinetic codes. However, there has been a growing interest… read more here.
Keywords: learning applications; infrastructures deep; deep learning; fusion ... See more keywords
Machine learning and applications in microbiology
Sign Up to like & getrecommendations! Published in 2021 at "FEMS Microbiology Reviews"
DOI: 10.1093/femsre/fuab015
Abstract: ABSTRACT To understand the intricacies of microorganisms at the molecular level requires making sense of copious volumes of data such that it may now be humanly impossible to detect insightful data patterns without an artificial… read more here.
Keywords: microbiology; learning applications; machine learning; applications microbiology ... See more keywords
A Novel Technique to Support Deep Learning Applications in a Model-Based Embedded Software Design Methodology
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Access"
DOI: 10.1109/access.2023.3281913
Abstract: As deep learning applications are getting popular in embedded systems, how to support deep learning applications in the model-based embedded software design methodology becomes a challenging problem. A previous solution is to represent each deep… read more here.
Keywords: software; methodology; support deep; learning applications ... See more keywords
Machine learning applications in epilepsy
Sign Up to like & getrecommendations! Published in 2019 at "Epilepsia"
DOI: 10.1111/epi.16333
Abstract: Machine learning leverages statistical and computer science principles to develop algorithms capable of improving performance through interpretation of data rather than through explicit instructions. Alongside widespread use in image recognition, language processing, and data mining,… read more here.
Keywords: applications epilepsy; machine; learning applications; machine learning ... See more keywords
Data science, learning, and applications to biomedical and health sciences
Sign Up to like & getrecommendations! Published in 2017 at "Annals of the New York Academy of Sciences"
DOI: 10.1111/nyas.13309
Abstract: The last decade has seen an unprecedented increase in the volume and variety of electronic data related to research and development, health records, and patient selfâtracking, collectively referred to as Big Data. Properly harnessed, Big… read more here.
Keywords: big data; learning applications; science learning; data science ... See more keywords
PROBLEM-BASED LEARNING APPLICATIONS IN ONLINE ENVIRONMENTS
Sign Up to like & getrecommendations! Published in 2023 at "Canadian Journal of Physics"
DOI: 10.1139/cjp-2022-0239
Abstract: Online learning environments have been used intensively during the Covid 19 pandemic and are frequently preferred alternative learning environments afterward. On the other hand, the lack of adequate learning applications for online environments negatively affects… read more here.
Keywords: online environments; learning environments; applications online; online learning ... See more keywords
Deep learning applications in clinical ophthalmology.
Sign Up to like & getrecommendations! Published in 2022 at "Journal of vision"
DOI: 10.1167/jov.22.3.40
Abstract: Rapid advances in retinal imaging technology combined with deep learning approaches for image analysis have provided new avenues of investigation in ophthalmic disease. First, deep learning provides a de novo approach to image analysis, identifying… read more here.
Keywords: clinical ophthalmology; applications clinical; ophthalmology; learning applications ... See more keywords
Machine Learning Applications of Surgical Imaging for the Diagnosis and Treatment of Spine Disorders: Current State of the Art.
Sign Up to like & getrecommendations! Published in 2022 at "Neurosurgery"
DOI: 10.1227/neu.0000000000001853
Abstract: Recent developments in machine learning (ML) methods demonstrate unparalleled potential for application in the spine. The ability for ML to provide diagnostic faculty, produce novel insights from existing capabilities, and augment or accelerate elements of… read more here.
Keywords: surgical imaging; learning applications; machine; applications surgical ... See more keywords
Machine Learning Applications in Solid Organ Transplantation and Related Complications
Sign Up to like & getrecommendations! Published in 2021 at "Frontiers in Immunology"
DOI: 10.3389/fimmu.2021.739728
Abstract: The complexity of transplant medicine pushes the boundaries of innate, human reasoning. From networks of immune modulators to dynamic pharmacokinetics to variable postoperative graft survival to equitable allocation of scarce organs, machine learning promises to… read more here.
Keywords: machine; learning applications; machine learning; solid organ ... See more keywords
Machine Learning Applications in the Neuro ICU: A Solution to Big Data Mayhem?
Sign Up to like & getrecommendations! Published in 2020 at "Frontiers in Neurology"
DOI: 10.3389/fneur.2020.554633
Abstract: The neurological ICU (neuro ICU) often suffers from significant limitations due to scarce resource availability for their neurocritical care patients. Neuro ICU patients require frequent neurological evaluations, continuous monitoring of various physiological parameters, frequent imaging,… read more here.
Keywords: applications neuro; neuro icu; learning applications; machine learning ... See more keywords