AIMC Topic: Markov Chains

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Scanpath modeling and classification with hidden Markov models.

Behavior research methods Feb 1, 2018
How people look at visual information reveals fundamental information about them; their interests and their states of mind. Previous studies showed that scanpath, i.e., the sequence of eye movements made by an observer exploring a visual stimulus, ca...
Humans Machine Learning Eye Movements Task Performance and Analysis Photic Stimulation Fixation, Ocular Markov Chains Individuality Probability
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SVM-dependent pairwise HMM: an application to protein pairwise alignments.

Bioinformatics (Oxford, England) Dec 15, 2017
MOTIVATION: Methods able to provide reliable protein alignments are crucial for many bioinformatics applications. In the last years many different algorithms have been developed and various kinds of information, from sequence conservation to secondar...
Sequence Alignment Sequence Analysis, Protein Algorithms Support Vector Machine Proteins Software Markov Chains Protein Structure, Secondary
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A transfer learning approach to goodness of pronunciation based automatic mispronunciation detection.

The Journal of the Acoustical Society of America Nov 1, 2017
Goodness of pronunciation (GOP) is the most widely used method for automatic mispronunciation detection. In this paper, a transfer learning approach to GOP based mispronunciation detection when applying maximum F1-score criterion (MFC) training to de...
Software Deep Learning Signal Processing, Computer-Assisted Humans Pattern Recognition, Automated Judgment Speech Perception Acoustics Markov Chains Speech Production Measurement Voice Quality Phonetics Speech Acoustics
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Application of supervised machine learning algorithms for the classification of regulatory RNA riboswitches.

Briefings in functional genomics Mar 1, 2017
Riboswitches, the small structured RNA elements, were discovered about a decade ago. It has been the subject of intense interest to identify riboswitches, understand their mechanisms of action and use them in genetic engineering. The accumulation of ...
Riboswitch Algorithms Models, Theoretical Supervised Machine Learning Markov Chains Bayes Theorem Humans
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Segmentation of organs-at-risks in head and neck CT images using convolutional neural networks.

Medical physics Feb 1, 2017
PURPOSE: Accurate segmentation of organs-at-risks (OARs) is the key step for efficient planning of radiation therapy for head and neck (HaN) cancer treatment. In the work, we proposed the first deep learning-based algorithm, for segmentation of OARs ...
Observer Variation Radiotherapy, Intensity-Modulated Radiotherapy Planning, Computer-Assisted Markov Chains Software Tomography, X-Ray Computed Head and Neck Neoplasms Humans Organs at Risk Image Processing, Computer-Assisted Neural Networks, Computer
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Modeling Movement Primitives with Hidden Markov Models for Robotic and Biomedical Applications.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2017
Movement primitives are elementary motion units and can be combined sequentially or simultaneously to compose more complex movement sequences. A movement primitive timeseries consist of a sequence of motion phases. This progression through a set of m...
Humans Algorithms Movement Models, Statistical Robotics Markov Chains Gait Pattern Recognition, Automated
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Towards sophisticated learning from EHRs: increasing prediction specificity and accuracy using clinically meaningful risk criteria.

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
Computer based analysis of Electronic Health Records (EHRs) has the potential to provide major novel insights of benefit both to specific individuals in the context of personalized medicine, as well as on the level of population-wide health care and ...
Markov Chains Electronic Health Records Humans Risk Algorithms Sensitivity and Specificity Stroke
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Reinforcement learning improves behaviour from evaluative feedback.

Nature May 28, 2015
Reinforcement learning is a branch of machine learning concerned with using experience gained through interacting with the world and evaluative feedback to improve a system's ability to make behavioural decisions. It has been called the artificial in...
Markov Chains Artificial Intelligence Time Factors Reward Algorithms Monte Carlo Method Feedback Empirical Research
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Patient-specific early classification of multivariate observations.

International journal of data mining and bioinformatics Jan 1, 2015
Early classification of time series has been receiving a lot of attention recently. In this paper we present a model, which we call the Early Classification Model (ECM), that allows for early, accurate and patient-specific classification of multivari...
Computational Biology Support Vector Machine Markov Chains Diagnosis, Computer-Assisted Multiple Sclerosis Databases, Factual Humans Sepsis Multivariate Analysis Gene Expression Profiling
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