AIMC Topic:
Supervised Machine Learning

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Feasibility of Active Machine Learning for Multiclass Compound Classification.

Journal of chemical information and modeling Jan 7, 2016
A common task in the hit-to-lead process is classifying sets of compounds into multiple, usually structural classes, which build the groundwork for subsequent SAR studies. Machine learning techniques can be used to automate this process by learning c...
Drug Discovery Feasibility Studies Supervised Machine Learning Humans Feedback Animals
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Self-Trained LMT for Semisupervised Learning.

Computational intelligence and neuroscience Dec 29, 2015
The most important asset of semisupervised classification methods is the use of available unlabeled data combined with a clearly smaller set of labeled examples, so as to increase the classification accuracy compared with the default procedure of sup...
Algorithms Learning Logistic Models Humans Self-Control Benchmarking Supervised Machine Learning
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Generalization Bounds Derived IPM-Based Regularization for Domain Adaptation.

Computational intelligence and neuroscience Dec 27, 2015
Domain adaptation has received much attention as a major form of transfer learning. One issue that should be considered in domain adaptation is the gap between source domain and target domain. In order to improve the generalization ability of domain ...
Models, Theoretical Humans Regression Analysis Artificial Intelligence Probability Supervised Machine Learning Generalization, Psychological Transfer, Psychology
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Stabilizing l1-norm prediction models by supervised feature grouping.

Journal of biomedical informatics Dec 9, 2015
Emerging Electronic Medical Records (EMRs) have reformed the modern healthcare. These records have great potential to be used for building clinical prediction models. However, a problem in using them is their high dimensionality. Since a lot of infor...
Models, Statistical Supervised Machine Learning Medical Informatics Humans Electronic Health Records
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Supervised learning for neural manifold using spatiotemporal brain activity.

Journal of neural engineering Nov 18, 2015
OBJECTIVE: Determining the means by which perceived stimuli are compactly represented in the human brain is a difficult task. This study aimed to develop techniques for the construction of the neural manifold as a representation of visual stimuli.
Time Factors Supervised Machine Learning Photic Stimulation Adult Male Magnetoencephalography Orientation Humans Brain Female Young Adult
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Interactive Cell Segmentation Based on Active and Semi-Supervised Learning.

IEEE transactions on medical imaging Oct 26, 2015
Automatic cell segmentation can hardly be flawless due to the complexity of image data particularly when time-lapse experiments last for a long time without biomarkers. To address this issue, we propose an interactive cell segmentation method by clas...
Supervised Machine Learning Microscopy Algorithms Image Processing, Computer-Assisted Cytological Techniques Humans
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Learning Spatiotemporally Encoded Pattern Transformations in Structured Spiking Neural Networks.

Neural computation Oct 23, 2015
Information encoding in the nervous system is supported through the precise spike timings of neurons; however, an understanding of the underlying processes by which such representations are formed in the first place remains an open question. Here we ...
Neural Networks, Computer Learning Neuronal Plasticity Action Potentials Supervised Machine Learning Neurons
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Voxel-based Gaussian naïve Bayes classification of ischemic stroke lesions in individual T1-weighted MRI scans.

Journal of neuroscience methods Oct 1, 2015
BACKGROUND: Manual lesion delineation by an expert is the standard for lesion identification in MRI scans, but it is time-consuming and can introduce subjective bias. Alternative methods often require multi-modal MRI data, user interaction, scans fro...
Brain Ischemia Image Interpretation, Computer-Assisted Bayes Theorem Stroke Supervised Machine Learning Magnetic Resonance Imaging Chronic Disease Reproducibility of Results Aged Young Adult Adult Humans Male Brain Middle Aged Female
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A bifurcation identifier for IV-OCT using orthogonal least squares and supervised machine learning.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Sep 21, 2015
Intravascular optical coherence tomography (IV-OCT) is an in-vivo imaging modality based on the intravascular introduction of a catheter which provides a view of the inner wall of blood vessels with a spatial resolution of 10-20 μm. Recent studies in...
Tomography, Optical Coherence Sensitivity and Specificity Image Enhancement Least-Squares Analysis Supervised Machine Learning Data Interpretation, Statistical Humans Coronary Artery Disease Image Interpretation, Computer-Assisted Radiography Reproducibility of Results Pattern Recognition, Automated
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A Method for Automatic and Objective Scoring of Bradykinesia Using Orientation Sensors and Classification Algorithms.

IEEE transactions on bio-medical engineering Sep 18, 2015
Correct assessment of bradykinesia is a key element in the diagnosis and monitoring of Parkinson's disease. Its evaluation is based on a careful assessment of symptoms and it is quantified using rating scales, where the Movement Disorders Society-Spo...
Hypokinesia Female Aged Male Middle Aged Humans Parkinson Disease Diagnosis, Computer-Assisted Support Vector Machine Supervised Machine Learning Fingers
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