Machine Learning Approaches for Thermoelectric Materials Research
Sign Up to like & getrecommendations! Published in 2019 at "Advanced Functional Materials"
DOI: 10.1002/adfm.201906041
Abstract: Thermoelectric (TE) materials provide a solid‐state solution in waste heat recovery and refrigeration. During the past few decades, considerable effort has been devoted towards improving the performance of TE materials, which requires the optimization of… read more here.
Keywords: thermoelectric materials; machine; machine learning; learning approaches ... See more keywords
Deep learning approaches for detection and removal of ghosting artifacts in MR spectroscopy
Sign Up to like & getrecommendations! Published in 2018 at "Magnetic Resonance in Medicine"
DOI: 10.1002/mrm.27096
Abstract: To make use of deep learning (DL) methods to detect and remove ghosting artifacts in clinical magnetic resonance spectra of human brain. read more here.
Keywords: deep learning; learning approaches; approaches detection; spectroscopy ... See more keywords
Jointly estimating parametric maps of multiple diffusion models from undersampled q‐space data: A comparison of three deep learning approaches
Sign Up to like & getrecommendations! Published in 2022 at "Magnetic Resonance in Medicine"
DOI: 10.1002/mrm.29162
Abstract: While advanced diffusion techniques have been found valuable in many studies, their clinical availability has been hampered partly due to their long scan times. Moreover, each diffusion technique can only extract a few relevant microstructural… read more here.
Keywords: maps multiple; diffusion; learning approaches; parametric maps ... See more keywords
Predicting DPP-IV inhibitors with machine learning approaches
Sign Up to like & getrecommendations! Published in 2017 at "Journal of Computer-Aided Molecular Design"
DOI: 10.1007/s10822-017-0009-6
Abstract: Dipeptidyl peptidase IV (DPP-IV) is a promising Type 2 diabetes mellitus (T2DM) drug target. DPP-IV inhibitors prolong the action of glucagon-like peptide-1 (GLP-1) and gastric inhibitory peptide (GIP), improve glucose homeostasis without weight gain, edema,… read more here.
Keywords: machine learning; dpp inhibitors; learning approaches; dpp ... See more keywords
Effects of Analogical Learning Approaches and Presentation Modalities on Ninth Graders’ Learning Outcome and Eye Movements: a Preliminary Study
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Science Education and Technology"
DOI: 10.1007/s10956-020-09835-7
Abstract: This study analyzed the impact of different analogical learning approaches (analogies or metaphors) integrated with different presentation modalities (pictures or texts) on middle school students’ learning performance of electricity with supporting evidence from their eye… read more here.
Keywords: analogical learning; learning approaches; electricity; presentation modalities ... See more keywords
Hybrid wavelet packet machine learning approaches for drought modeling
Sign Up to like & getrecommendations! Published in 2020 at "Environmental Earth Sciences"
DOI: 10.1007/s12665-020-08971-y
Abstract: Among all the natural disasters, drought has the most catastrophic encroachment on the surrounding and environment. Gulbarga, one of the semi-arid districts of Karnataka state, India receives about 700 mm of average annual rainfall and… read more here.
Keywords: learning approaches; machine learning; wavelet packet; drought ... See more keywords
Advanced EEG-based learning approaches to predict schizophrenia: Promises and pitfalls
Sign Up to like & getrecommendations! Published in 2021 at "Artificial intelligence in medicine"
DOI: 10.1016/j.artmed.2021.102039
Abstract: The complexity and heterogeneity of schizophrenia symptoms challenge an objective diagnosis, which is typically based on behavioral and clinical manifestations. Moreover, the boundaries of schizophrenia are not precisely demarcated from other nosologic categories, such as… read more here.
Keywords: schizophrenia; based learning; approaches predict; eeg based ... See more keywords
An exploration on the machine learning approaches to determine the erosion rates for liquid hydrocarbon transmission pipelines towards safer and cleaner transportations
Sign Up to like & getrecommendations! Published in 2021 at "Journal of Cleaner Production"
DOI: 10.1016/j.jclepro.2021.126478
Abstract: Abstract Erosion is commonly found in pipelines with existence of interactions between solid particles, fluid product transported and the surrounding materials. Erosion may lead to material degradation in pipeline and may eventually cause pipeline failure.… read more here.
Keywords: pipeline; erosion; erosion rate; learning approaches ... See more keywords
Effective deep learning approaches for summarization of legal texts
Sign Up to like & getrecommendations! Published in 2019 at "Journal of King Saud University - Computer and Information Sciences"
DOI: 10.1016/j.jksuci.2019.11.015
Abstract: Abstract The availability of legal judgment documents in digital form offers numerous opportunities for information extraction and application. Automatic summarization of these legal texts is a crucial and a challenging task due to the unusual… read more here.
Keywords: approaches summarization; effective deep; deep learning; learning approaches ... See more keywords
Two decades of advances in muscle imaging in children: from pattern recognition of muscle diseases to quantification and machine learning approaches
Sign Up to like & getrecommendations! Published in 2021 at "Neuromuscular Disorders"
DOI: 10.1016/j.nmd.2021.08.006
Abstract: Muscle imaging has progressively gained popularity in the neuromuscular field. Together with detailed clinical examination and muscle biopsy, it has become one of the main tools for deep phenotyping and orientation of etiological diagnosis. Even… read more here.
Keywords: pattern recognition; machine learning; muscle; learning approaches ... See more keywords
Machine Learning Approaches for Analysis of Multiscale Imaging Data for Atmospheric and Soil Particles
Sign Up to like & getrecommendations! Published in 2019 at "Microscopy and Microanalysis"
DOI: 10.1017/s1431927619001703
Abstract: Bioaerosol and soil organic particles are ubiquitous in the atmosphere, and they are multicomponent and complex in nature [1-4]. Biological particles contribute to a major fraction of coarse mode particles, especially in the tropical areas,… read more here.
Keywords: soil; mixing state; soil organic; learning approaches ... See more keywords