AIMC Topic: Machine Learning

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A Spatiotemporal Convolutional Network for Multi-Behavior Recognition of Pigs.

Sensors (Basel, Switzerland) Apr 22, 2020
The statistical data of different kinds of behaviors of pigs can reflect their health status. However, the traditional behavior statistics of pigs were obtained and then recorded from the videos through human eyes. In order to reduce labor and time c...
Animals Swine Deep Learning Pattern Recognition, Automated Neural Networks, Computer Machine Learning Algorithms
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Classifying heterogeneous presentations of PTSD via the default mode, central executive, and salience networks with machine learning.

NeuroImage. Clinical Apr 22, 2020
Intrinsic connectivity networks (ICNs), including the default mode network (DMN), the central executive network (CEN), and the salience network (SN) have been shown to be aberrant in patients with posttraumatic stress disorder (PTSD). The purpose of ...
Middle Aged Amygdala Humans Brain Mapping Female Stress Disorders, Post-Traumatic Dissociative Disorders Machine Learning Neural Pathways Emotions Brain Nerve Net Adult Male
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Propensity score adjustment using machine learning classification algorithms to control selection bias in online surveys.

PloS one Apr 22, 2020
Modern survey methods may be subject to non-observable bias, from various sources. Among online surveys, for example, selection bias is prevalent, due to the sampling mechanism commonly used, whereby participants self-select from a subgroup whose cha...
Machine Learning Algorithms Research Design Humans Data Interpretation, Statistical Computer Simulation Surveys and Questionnaires Selection Bias Logistic Models Propensity Score
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Phase portraits as movement primitives for fast humanoid robot control.

Neural networks : the official journal of the International Neural Network Society Apr 21, 2020
Currently, usual approaches for fast robot control are largely reliant on solving online optimal control problems. Such methods are known to be computationally intensive and sensitive to model accuracy. On the other hand, animals plan complex motor a...
Machine Learning Learning Biomechanical Phenomena Humans Robotics Motor Skills
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Detection and identification of Cannabis sativa L. using near infrared hyperspectral imaging and machine learning methods. A feasibility study.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Apr 21, 2020
Remote identification of illegal plantations of Cannabis sativa Linnaeus is an important task for the Brazilian Federal Police. The current analytical methodology is expensive and strongly dependent on the expertise of the forensic investigator. A fa...
Principal Component Analysis Hyperspectral Imaging Feasibility Studies Cheminformatics Machine Learning Brazil Reproducibility of Results Spectroscopy, Near-Infrared Sensitivity and Specificity Cannabis Plant Leaves
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Association Rule Learning Is an Easy and Efficient Method for Identifying Profiles of Traumas and Stressors that Predict Psychopathology in Disaster Survivors: The Example of Sri Lanka.

International journal of environmental research and public health Apr 21, 2020
Research indicates that psychopathology in disaster survivors is a function of both experienced trauma and stressful life events. However, such studies are of limited utility to practitioners who are about to go into a new post-disaster setting as (1...
Humans Sri Lanka Machine Learning Disasters Mental Disorders Survivors Stress Disorders, Post-Traumatic
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gammaBOriS: Identification and Taxonomic Classification of Origins of Replication in Gammaproteobacteria using Motif-based Machine Learning.

Scientific reports Apr 21, 2020
The biology of bacterial cells is, in general, based on information encoded on circular chromosomes. Regulation of chromosome replication is an essential process that mostly takes place at the origin of replication (oriC), a locus unique per chromoso...
Software Phylogeny Models, Genetic Base Sequence Machine Learning Nucleotide Motifs Replication Origin Consensus Sequence Gammaproteobacteria
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Application of a convolutional neural network for predicting the occurrence of ventricular tachyarrhythmia using heart rate variability features.

Scientific reports Apr 21, 2020
Predicting the occurrence of ventricular tachyarrhythmia (VTA) in advance is a matter of utmost importance for saving the lives of cardiac arrhythmia patients. Machine learning algorithms have been used to predict the occurrence of imminent VTA. In t...
Arrhythmias, Cardiac Heart Rate Tachycardia, Ventricular Male Middle Aged Support Vector Machine Machine Learning Algorithms Female Prognosis Humans Aged Neural Networks, Computer Adult
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Machine Learning Algorithms in Suicide Prevention: Clinician Interpretations as Barriers to Implementation.

The Journal of clinical psychiatry Apr 21, 2020
OBJECTIVE: Machine learning algorithms in electronic medical records can classify patients by suicide risk, but no research has explored clinicians' perceptions of suicide risk flags generated by these algorithms, which may affect algorithm implement...
False Negative Reactions False Positive Reactions Female Adult Male Risk Assessment Attitude of Health Personnel Suicide Prevention Health Personnel Physicians Electronic Health Records Humans Machine Learning Algorithms
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Natural Language Generation Model for Mammography Reports Simulation.

IEEE journal of biomedical and health informatics Apr 20, 2020
Extending the size of labeled corpora of medical reports is a major step towards a successful training of machine learning algorithms. Simulating new text reports is a key solution for reports augmentation, which extends the cohort size. However, tex...
Humans Neural Networks, Computer Machine Learning Mammography Algorithms Language Natural Language Processing
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