AIMC Topic: Algorithms

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Learning a discriminant graph-based embedding with feature selection for image categorization.

Neural networks : the official journal of the International Neural Network Society Dec 27, 2018
Graph-based embedding methods are very useful for reducing the dimension of high-dimensional data and for extracting their relevant features. In this paper, we introduce a novel nonlinear method called Flexible Discriminant graph-based Embedding with...
Photic Stimulation Humans Algorithms Supervised Machine Learning Pattern Recognition, Automated
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The analysis of the effects of acute rheumatic fever in childhood on cardiac disease with data mining.

International journal of medical informatics Dec 27, 2018
BACKGROUND: Acute rheumatic fever (ARF) is an important disease that is frequently seen in Turkey, it is necessary to develop solutions to cure the disease. It is believed that new data analysis methods may be applied to this disease, and this may be...
Humans Algorithms Bayes Theorem Data Mining Child, Preschool Female Heart Diseases Child Male Decision Trees Adolescent Rheumatic Fever
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Geometrical features for premature ventricular contraction recognition with analytic hierarchy process based machine learning algorithms selection.

Computer methods and programs in biomedicine Dec 27, 2018
BACKGROUND AND OBJECTIVE: Premature ventricular contraction is associated to the risk of coronary heart disease, and its diagnosis depends on a long time heart monitoring. For this purpose, monitoring through Holter devices is often used and computat...
Ventricular Premature Complexes Wavelet Analysis Diagnosis, Computer-Assisted Electrocardiography Signal-To-Noise Ratio Machine Learning Algorithms Humans Neural Networks, Computer
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Prediction of sepsis patients using machine learning approach: A meta-analysis.

Computer methods and programs in biomedicine Dec 26, 2018
STUDY OBJECTIVE: Sepsis is a common and major health crisis in hospitals globally. An innovative and feasible tool for predicting sepsis remains elusive. However, early and accurate prediction of sepsis could help physicians with proper treatments an...
Algorithms Forecasting Sepsis Area Under Curve Humans Machine Learning
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Predicting persistent depressive symptoms in older adults: A machine learning approach to personalised mental healthcare.

Journal of affective disorders Dec 25, 2018
BACKGROUND: Depression causes significant physical and psychosocial morbidity. Predicting persistence of depressive symptoms could permit targeted prevention, and lessen the burden of depression. Machine learning is a rapidly expanding field, and suc...
Predictive Value of Tests Follow-Up Studies Age Factors Psychiatric Status Rating Scales Delivery of Health Care Algorithms Depression Female Decision Support Techniques Logistic Models Humans Aged Machine Learning Aged, 80 and over Male Risk Assessment
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Infrared Spectral Characteristics of Electrical Injuries on Swine Skin Caused by Different Voltages Based on Machine Learning Algorithms.

Fa yi xue za zhi Dec 25, 2018
OBJECTIVES: To explore infrared spectrum characteristics of different voltages induced electrical injuries on swine skin by using Fourier transform infrared-microspectroscopy （FTIR-MSP） combined with machine learning algorithms, thus to provide a ref...
Least-Squares Analysis Discriminant Analysis Animals Skin Burns, Electric Machine Learning Swine Spectroscopy, Fourier Transform Infrared Algorithms
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Cardiac Phase Detection in Echocardiograms With Densely Gated Recurrent Neural Networks and Global Extrema Loss.

IEEE transactions on medical imaging Dec 24, 2018
Accurate detection of end-systolic (ES) and end-diastolic (ED) frames in an echocardiographic cine series can be difficult but necessary pre-processing step for the development of automatic systems to measure cardiac parameters. The detection task is...
Humans Algorithms Image Processing, Computer-Assisted Echocardiography Heart Deep Learning Myocardial Contraction
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Deep Convolutional Neural Networks for Feature-Less Automatic Classification of Independent Components in Multi-Channel Electrophysiological Brain Recordings.

IEEE transactions on bio-medical engineering Dec 24, 2018
OBJECTIVE: Interpretation of the electroencephalographic (EEG) and magnetoencephalographic (MEG) signals requires off-line artifacts removal. Since artifacts share frequencies with brain activity, filtering is insufficient. Blind source separation, m...
Artifacts Humans Magnetoencephalography Deep Learning Algorithms Electroencephalography Brain Signal Processing, Computer-Assisted
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Prediction of matrix metal proteinases-12 inhibitors by machine learning approaches.

Journal of biomolecular structure & dynamics Dec 24, 2018
Matrix metal proteinases-12 (MMP-12) is a hot pharmaceutical target on the treatment of many human diseases. There's a crying need for designing and finding new MMP-12 inhibitors. In this work, four machine learning approaches, support vector machine...
Algorithms Reproducibility of Results Drug Discovery Quantitative Structure-Activity Relationship ROC Curve Machine Learning Matrix Metalloproteinase Inhibitors Support Vector Machine Matrix Metalloproteinase 12 Molecular Structure
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iRNA-PseKNC(2methyl): Identify RNA 2'-O-methylation sites by convolution neural network and Chou's pseudo components.

Journal of theoretical biology Dec 24, 2018
The 2'-O-methylation transferase is involved in the process of 2'-O-methylation. In catalytic processes, the 2-hydroxy group of the ribose moiety of a nucleotide accept a methyl group. This methylation process is a post-transcriptional modification, ...
Machine Learning Algorithms Deep Learning Humans Neural Networks, Computer Binding Sites Computational Biology RNA Methylation
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