AIMC Topic:
Supervised Machine Learning

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Development of a Late-Life Dementia Prediction Index with Supervised Machine Learning in the Population-Based CAIDE Study.

Journal of Alzheimer's disease : JAD Jan 1, 2017
BACKGROUND AND OBJECTIVE: This study aimed to develop a late-life dementia prediction model using a novel validated supervised machine learning method, the Disease State Index (DSI), in the Finnish population-based CAIDE study.
Dementia ROC Curve Cognition Aged Male Severity of Illness Index Humans Neuropsychological Tests Retrospective Studies Finland Female Reproducibility of Results Apolipoproteins E Risk Factors Community Health Planning Predictive Value of Tests Supervised Machine Learning Cerebrovascular Disorders
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Similarity measurement of lung masses for medical image retrieval using kernel based semisupervised distance metric.

Medical physics Dec 1, 2016
PURPOSE: To develop a new algorithm to measure the similarity between the query lung mass and reference lung mass data set for content-based medical image retrieval (CBMIR).
Supervised Machine Learning Image Processing, Computer-Assisted Humans Lung Neoplasms Databases, Factual Diagnostic Imaging
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A supervised learning rule for classification of spatiotemporal spike patterns.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Aug 1, 2016
This study introduces a novel supervised algorithm for spiking neurons that take into consideration synapse delays and axonal delays associated with weights. It can be utilized for both classification and association and uses several biologically inf...
Action Potentials Supervised Machine Learning Neurons Algorithms Models, Neurological Synapses
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Fall risk probability estimation based on supervised feature learning using public fall datasets.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Aug 1, 2016
Risk of falling is considered among major threats for elderly population and therefore started to play an important role in modern healthcare. With recent development of sensor technology, the number of studies dedicated to reliable fall detection sy...
Risk Assessment Accidental Falls Models, Statistical Supervised Machine Learning Humans Algorithms Probability
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Using Supervised Machine Learning to Classify Real Alerts and Artifact in Online Multisignal Vital Sign Monitoring Data.

Critical care medicine Jul 1, 2016
OBJECTIVE: The use of machine-learning algorithms to classify alerts as real or artifacts in online noninvasive vital sign data streams to reduce alarm fatigue and missed true instability.
Oximetry Supervised Machine Learning Heart Rate Artifacts Vital Signs Respiratory Rate Clinical Alarms Cohort Studies Blood Pressure Determination Monitoring, Physiologic Humans
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Arrangement and Applying of Movement Patterns in the Cerebellum Based on Semi-supervised Learning.

Cerebellum (London, England) Jun 1, 2016
Biological control systems have long been studied as a possible inspiration for the construction of robotic controllers. The cerebellum is known to be involved in the production and learning of smooth, coordinated movements. Therefore, highly regular...
Cerebellum Movement Supervised Machine Learning Humans Neurons Models, Neurological
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Spiking neurons can discover predictive features by aggregate-label learning.

Science (New York, N.Y.) Mar 4, 2016
The brain routinely discovers sensory clues that predict opportunities or dangers. However, it is unclear how neural learning processes can bridge the typically long delays between sensory clues and behavioral outcomes. Here, I introduce a learning c...
Humans Neural Networks, Computer Brain Learning Reinforcement, Psychology Supervised Machine Learning Formative Feedback Speech Neurons Membrane Potentials Concept Formation Models, Neurological Unsupervised Machine Learning
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Mastering the game of Go with deep neural networks and tree search.

Nature Jan 28, 2016
The game of Go has long been viewed as the most challenging of classic games for artificial intelligence owing to its enormous search space and the difficulty of evaluating board positions and moves. Here we introduce a new approach to computer Go th...
Humans Neural Networks, Computer Monte Carlo Method Computers Software Games, Recreational Reinforcement, Psychology Europe Supervised Machine Learning
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Google AI algorithm masters ancient game of Go.

Nature Jan 28, 2016
Reinforcement, Psychology Games, Recreational Supervised Machine Learning Biomimetics Goals Neural Networks, Computer Software Decision Making Humans
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Supervised learning technique for the automated identification of white matter hyperintensities in traumatic brain injury.

Brain injury Jan 1, 2016
BACKGROUND: White matter hyperintensities (WMHs) are foci of abnormal signal intensity in white matter regions seen with magnetic resonance imaging (MRI). WMHs are associated with normal ageing and have shown prognostic value in neurological conditio...
Image Interpretation, Computer-Assisted Adolescent Electronic Data Processing Adult Cohort Studies Humans White Matter Male Female Magnetic Resonance Imaging Middle Aged Young Adult Brain Injuries, Traumatic Brain Mapping Supervised Machine Learning
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