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From genetic correlations of Alzheimer’s disease to classification with artificial neural network models
Sporadic Alzheimer’s disease (AD) is a complex neurological disorder characterized by many risk loci with potential associations with different...
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Artificial Neural Networks
This chapter shows the basic structure and function of a simple neural network as well as some examples where Artificial Neural Networks can be...
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A novel probabilistic intermittent neural network (PINN) and artificial jelly fish optimization (AJFO)-based plant leaf disease detection system
Plant leaf disease identification and classification are the most essential and demanding tasks in the agriculture field. In traditional researches,...
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An artificial neural network model based on autophagy-related genes in childhood systemic lupus erythematosus
BackgroundChildhood systemic lupus erythematosus (cSLE) is a multisystemic, life-threatening autoimmune disease. Compared to adults, SLE in childhood...
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Discriminating two bacteria via laser-induced breakdown spectroscopy and artificial neural network
Rapid and successful clinical diagnosis and bacterial infection treatment depend on accurate identification and differentiation between different...
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An artificial neural network explains how bats might use vision for navigation
Animals navigate using various sensory information to guide their movement. Miniature tracking devices now allow documenting animals’ routes with...
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Cross-grain fracture characterization in softwood using artificial neural network analysis of acoustic emissions
In an effort to better understand crack growth in the cross-grain direction, an acoustic emission (AE) approach was implemented to monitor the...
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Prediction of the color change of surface thermally treated wood by artificial neural network
Surface thermal treatment (STT) can achieve efficient and successful thermal modification on wood surfaces, resulting in a beautiful, natural,...
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Response surface methodology (RSM) and artificial neural network (ANN) integrated optimization for lipase production by
Bacillus holotolerans Response surface methodology (RSM) and artificial neural networks (ANN) are considered the most efficient way for optimization and modeling studies...
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Neural encoding with unsupervised spiking convolutional neural network
Accurately predicting the brain responses to various stimuli poses a significant challenge in neuroscience. Despite recent breakthroughs in neural...
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Electrochemical Immunosensor in Combination with an Artificial Neural Network Study for Pathogenic Bacteria Detection using a Modified Glassy Carbon Electrode
We report here the results of studies related to the fabrication of an electrochemical immunosensor for the detection of Escherichia coli ATCC 25922...
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Optimization of preparation conditions for Salsola laricifolia protoplasts using response surface methodology and artificial neural network modeling
BackgroundSalsola laricifolia is a typical C 3 –C 4 typical desert plant, belonging to the family Amaranthaceae . An efficient single-cell system is...
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Neural Network-Based Decoding Input Stimulus Data Based on Recurrent Neural Network Neural Activity Pattern
AbstractThe paper reports the assessment of the possibility to recover information obtained using an artificial neural network via inspecting neural...
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ARIMAX—Artificial neural network hybrid model for predicting semilooper (Chrysodeixis acuta) incidence on soybean
Insect pest and weather relations analysed using statistical models empower crop pest management through their capacity to forewarn abundance or...
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The Application of Chemometric Methods in the Production of Enzymes Through Solid State Fermentation Uses the Artificial Neural Network—a Review
In the last decade, different multivariate statistical techniques have been applied to assist enzymatic production by microorganisms through solid...
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Enhanced biosynthesis of coated silver nanoparticles using isolated bacteria from heavy metal soils and their photothermal-based antibacterial activity: integrating Response Surface Methodology (RSM) Hybrid Artificial Neural Network (ANN)-Genetic Algorithm (GA) strategies
This study explores the biosynthesis of silver nanoparticles (AgNPs) using the Streptomyces tuirus S16 strain, presenting an eco-friendly alternative...
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Estimation of Eucalyptus productivity using efficient artificial neural network
Prediction of plantation productivity from environmental data is challenged by the complex relationships defining the growth and yield processes....
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Control of system parameters by estimating screw withdrawal strength values of particleboards using artificial neural network-based statistical control charts
In this study, with data obtained from a particleboard factory, screw withdrawal strength (SWS) values of particleboards were estimated using...
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Artificial neural network modeling to predict and optimize phenolic acid production from callus culture of Lactuca undulata Ledeb.
The present study aims to model and optimize phenolic acid production from Lactuca undulate Ledeb. root- and leaf-derived callus using the...
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Eutrophication Modeling of Chilika Lagoon Using an Artificial Neural Network Approach
Chilika lagoon is the first Ramsar site in India located along the East Coast. Prediction of the eutrophication of such ecosystems is a key approach...