AIMC Topic:
Computer Simulation

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Bypassing the volume conduction effect by multilayer neural network for effective connectivity estimation.

Medical & biological engineering & computing Jul 4, 2019
Differentiation of real interactions between different brain regions from spurious ones has been a challenge in neuroimaging researches. While using electroencephalographic data, those spurious interactions are mostly caused by the volume conduction ...
Humans Neural Networks, Computer Brain Mapping Electroencephalography Signal Processing, Computer-Assisted Algorithms Brain Computer Simulation
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Deep multiphysics: Coupling discrete multiphysics with machine learning to attain self-learning in-silico models replicating human physiology.

Artificial intelligence in medicine Jul 4, 2019
OBJECTIVES: The objective of this study is to devise a modelling strategy for attaining in-silico models replicating human physiology and, in particular, the activity of the autonomic nervous system.
Machine Learning Computer Simulation Feedback, Physiological Autonomic Nervous System Esophagus Deep Learning Algorithms Humans Physics Peristalsis Models, Biological Reinforcement, Psychology
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Efficiently searching through large tACS parameter spaces using closed-loop Bayesian optimization.

Brain stimulation Jul 4, 2019
BACKGROUND: Selecting optimal stimulation parameters from numerous possibilities is a major obstacle for assessing the efficacy of non-invasive brain stimulation.
Bayes Theorem Transcranial Direct Current Stimulation Phosphenes Female Young Adult Adult Male Humans Machine Learning Computer Simulation
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Machine learning prediction of cyanobacterial toxin (microcystin) toxicodynamics in humans.

ALTEX Jul 2, 2019
Microcystins (MC) represent a family of cyclic peptides with approx. 250 congeners presumed harmful to human health due to their ability to inhibit ser/thr-proteinphosphatases (PPP), albeit all hazard and risk assessments (RA) are based on data of on...
Phosphoprotein Phosphatases Animal Use Alternatives Molecular Structure Models, Biological Microcystins Computer Simulation Nuclear Proteins Humans Machine Learning
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Variable Selection for Nonparametric Learning with Power Series Kernels.

Neural computation Jul 1, 2019
In this letter, we propose a variable selection method for general nonparametric kernel-based estimation. The proposed method consists of two-stage estimation: (1) construct a consistent estimator of the target function, and (2) approximate the estim...
Diabetes Mellitus Machine Learning Statistics, Nonparametric Computer Simulation Humans Post-Cardiac Arrest Syndrome Female Logistic Models Adult Renal Insufficiency, Chronic Neoplasms
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Learning Compositional Representations of Interacting Systems with Restricted Boltzmann Machines: Comparative Study of Lattice Proteins.

Neural computation Jul 1, 2019
A restricted Boltzmann machine (RBM) is an unsupervised machine learning bipartite graphical model that jointly learns a probability distribution over data and extracts their relevant statistical features. RBMs were recently proposed for characterizi...
Computer Simulation Models, Statistical Proteins Unsupervised Machine Learning Probability Principal Component Analysis Static Electricity Stochastic Processes Models, Molecular Sequence Alignment Amino Acid Sequence
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Approaching coupled cluster accuracy with a general-purpose neural network potential through transfer learning.

Nature communications Jul 1, 2019
Computational modeling of chemical and biological systems at atomic resolution is a crucial tool in the chemist's toolset. The use of computer simulations requires a balance between cost and accuracy: quantum-mechanical methods provide high accuracy ...
Neural Networks, Computer Machine Learning Thermodynamics Isomerism Computer Simulation Hydrocarbons Benchmarking
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A Ligand-Based Virtual Screening Method Using Direct Quantification of Generalization Ability.

Molecules (Basel, Switzerland) Jun 30, 2019
Machine learning plays an important role in ligand-based virtual screening. However, conventional machine learning approaches tend to be inefficient when dealing with such problems where the data are imbalanced and features describing the chemical ch...
HIV Integrase Computer Simulation Models, Chemical HIV-1 Machine Learning Ligands
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C-HMOSHSSA: Gene selection for cancer classification using multi-objective meta-heuristic and machine learning methods.

Computer methods and programs in biomedicine Jun 29, 2019
BACKGROUND AND OBJECTIVE: Over the last two decades, DNA microarray technology has emerged as a powerful tool for early cancer detection and prevention. It helps to provide a detailed overview of disease complex microenvironment. Moreover, online ava...
Early Detection of Cancer Gene Expression Heuristics Oligonucleotide Array Sequence Analysis Neoplasms Computational Biology Support Vector Machine Predatory Behavior Social Behavior Algorithms Female Humans Animals Databases, Factual Machine Learning Reproducibility of Results Male Computer Simulation Software Tumor Microenvironment Sensitivity and Specificity Biomarkers, Tumor
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Gene Expression Data Based Deep Learning Model for Accurate Prediction of Drug-Induced Liver Injury in Advance.

Journal of chemical information and modeling Jun 28, 2019
Drug-induced liver injury (DILI), one of the most common adverse effects, leads to drug development failure or withdrawal from the market in most cases, showing an emerging challenge that is to accurately predict DILI in the early stage. Recently, th...
Drug Discovery Rats Rats, Sprague-Dawley Chemical and Drug Induced Liver Injury Computer Simulation Models, Biological Structure-Activity Relationship Machine Learning Vinblastine Gene Expression Regulation Molecular Structure Reproducibility of Results Algorithms Animals Male
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