AIMC Topic: Machine Learning

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Machine Learning-Based Three-Dimensional Echocardiographic Quantification of Right Ventricular Size and Function: Validation Against Cardiac Magnetic Resonance.

Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography Jun 4, 2019
BACKGROUND: Three-dimensional echocardiography (3DE) allows accurate and reproducible measurements of right ventricular (RV) size and function. However, widespread implementation of 3DE in routine clinical practice is limited because the existing sof...
Humans Machine Learning Female Reproducibility of Results Heart Ventricles Image Interpretation, Computer-Assisted Magnetic Resonance Imaging, Cine Ventricular Function, Right Echocardiography, Three-Dimensional Male Middle Aged
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Applying Deep Neural Networks and Ensemble Machine Learning Methods to Forecast Airborne Pollen.

International journal of environmental research and public health Jun 4, 2019
Allergies to airborne pollen are a significant issue affecting millions of Americans. Consequently, accurately predicting the daily concentration of airborne pollen is of significant public benefit in providing timely alerts. This study presents a me...
Allergens Antigens, Plant Ambrosia Bayes Theorem Weather Neural Networks, Computer Machine Learning Forecasting Plant Extracts
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Machine Learning for Molecular Modelling in Drug Design.

Biomolecules Jun 4, 2019
Machine learning (ML) has become a crucial component of early drug discovery. This researcharea has been fueled by two main factors [...].
Machine Learning Drug Design Models, Molecular
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Error Tolerance of Machine Learning Algorithms across Contemporary Biological Targets.

Molecules (Basel, Switzerland) Jun 4, 2019
Machine learning continues to make strident advances in the prediction of desired properties concerning drug development. Problematically, the efficacy of machine learning in these arenas is reliant upon highly accurate and abundant data. These two l...
Reproducibility of Results Biomarkers, Tumor Drug Discovery Machine Learning Algorithms Workflow Models, Biological Molecular Targeted Therapy Antineoplastic Agents ROC Curve Bayes Theorem Humans Neural Networks, Computer
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Machine Learning Models Combined with Virtual Screening and Molecular Docking to Predict Human Topoisomerase I Inhibitors.

Molecules (Basel, Switzerland) Jun 4, 2019
In this work, random forest (RF), support vector machine, k-nearest neighbor and C4.5 decision tree, were used to establish classification models for predicting whether an unknown molecule is an inhibitor of human topoisomerase I (Top1) protein. All ...
Molecular Docking Simulation ROC Curve Molecular Structure Molecular Dynamics Simulation Quantitative Structure-Activity Relationship Topoisomerase I Inhibitors Humans Algorithms Machine Learning Computer Simulation Reproducibility of Results
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Atrophy of cerebellar peduncles in essential tremor: a machine learning-based volumetric analysis.

European radiology Jun 3, 2019
BACKGROUND: Subtle cerebellar signs are frequently observed in essential tremor (ET) and may be associated with cerebellar dysfunction. This study aims to evaluate the macrostructural integrity of the superior, middle, and inferior cerebellar peduncl...
Female Adult Male Humans Machine Learning Middle Aged Magnetic Resonance Imaging Gray Matter White Matter Atrophy Essential Tremor
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The application of machine learning methods for prediction of metal sorption onto biochars.

Journal of hazardous materials Jun 3, 2019
The adsorption of six heavy metals (lead, cadmium, nickel, arsenic, copper, and zinc) on 44 biochars were modeled using artificial neural network (ANN) and random forest (RF) based on 353 dataset of adsorption experiments from literatures. The regres...
Nerve Net Water Purification Biomass Water Pollutants, Chemical Hydrogen-Ion Concentration Machine Learning Adsorption Cations Wastewater Regression Analysis Metals, Heavy Charcoal
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Time series trend detection and forecasting using complex network topology analysis.

Neural networks : the official journal of the International Neural Network Society Jun 3, 2019
Extracting knowledge from time series provides important tools for many real applications. However, many challenging problems still open due to the stochastic nature of large amount of time series. Considering this scenario, new data mining and machi...
Machine Learning Forecasting Data Mining
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Hierarchical human-like strategy for aspect-level sentiment classification with sentiment linguistic knowledge and reinforcement learning.

Neural networks : the official journal of the International Neural Network Society Jun 3, 2019
Aspect-level sentiment analysis is a crucial problem in fine-grained sentiment analysis, which aims to automatically predict the sentiment polarity of the specific aspect in its context. Although remarkable progress has been made by deep learning bas...
Linguistics Reinforcement, Psychology Machine Learning Models, Neurological Knowledge Humans
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Margin-Based Pareto Ensemble Pruning: An Ensemble Pruning Algorithm That Learns to Search Optimized Ensembles.

Computational intelligence and neuroscience Jun 3, 2019
The ensemble pruning system is an effective machine learning framework that combines several learners as experts to classify a test set. Generally, ensemble pruning systems aim to define a region of competence based on the validation set to select th...
Pattern Recognition, Automated Algorithms Humans Scientific Experimental Error Computer Simulation Machine Learning Benchmarking
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