AIMC Topic:
Databases, Factual

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Neural Network-Based Coronary Heart Disease Risk Prediction Using Feature Correlation Analysis.

Journal of healthcare engineering Sep 6, 2017
BACKGROUND: Of the machine learning techniques used in predicting coronary heart disease (CHD), neural network (NN) is popularly used to improve performance accuracy.
Aged Republic of Korea Aged, 80 and over Nutrition Surveys Female Adult Coronary Artery Disease Risk Factors Humans Risk Assessment Male Neural Networks, Computer ROC Curve Middle Aged Databases, Factual
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Learning from Narrated Instruction Videos.

IEEE transactions on pattern analysis and machine intelligence Sep 5, 2017
Automatic assistants could guide a person or a robot in performing new tasks, such as changing a car tire or repotting a plant. Creating such assistants, however, is non-trivial and requires understanding of visual and verbal content of a video. Towa...
Cluster Analysis Narration Unsupervised Machine Learning Natural Language Processing Databases, Factual Internet Information Dissemination Video Recording
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Construction accident narrative classification: An evaluation of text mining techniques.

Accident; analysis and prevention Sep 1, 2017
Learning from past accidents is fundamental to accident prevention. Thus, accident and near miss reporting are encouraged by organizations and regulators. However, for organizations managing large safety databases, the time taken to accurately classi...
Databases, Factual Construction Industry Reproducibility of Results Humans Linear Models Accidents, Occupational Machine Learning Narration Algorithms Safety Bayes Theorem Data Mining Support Vector Machine Accidents Decision Trees
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Identifying sleep spindles with multichannel EEG and classification optimization.

Computers in biology and medicine Sep 1, 2017
Researchers classify critical neural events during sleep called spindles that are related to memory consolidation using the method of scalp electroencephalography (EEG). Manual classification is time consuming and is susceptible to low inter-rater ag...
Male Adolescent Models, Neurological Electroencephalography Databases, Factual Female Adult Signal Processing, Computer-Assisted Sleep Humans Machine Learning
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Automatic Categorization and Scoring of Solid, Part-Solid and Non-Solid Pulmonary Nodules in CT Images with Convolutional Neural Network.

Scientific reports Sep 1, 2017
We present a computer-aided diagnosis system (CADx) for the automatic categorization of solid, part-solid and non-solid nodules in pulmonary computerized tomography images using a Convolutional Neural Network (CNN). Provided with only a two-dimension...
Humans Neural Networks, Computer Diagnosis, Computer-Assisted Databases, Factual Lung Neoplasms Solitary Pulmonary Nodule Tomography, X-Ray Computed Diagnosis, Differential Lung
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Accurate Identification of Fatty Liver Disease in Data Warehouse Utilizing Natural Language Processing.

Digestive diseases and sciences Aug 31, 2017
INTRODUCTION: Natural language processing is a powerful technique of machine learning capable of maximizing data extraction from complex electronic medical records.
Fatty Liver United States Magnetic Resonance Imaging Data Mining United States Department of Veterans Affairs Humans Predictive Value of Tests Tomography, X-Ray Computed Algorithms Veterans Health Natural Language Processing Electronic Health Records Databases, Factual Prognosis Ultrasonography
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A deep convolutional neural network model to classify heartbeats.

Computers in biology and medicine Aug 24, 2017
The electrocardiogram (ECG) is a standard test used to monitor the activity of the heart. Many cardiac abnormalities will be manifested in the ECG including arrhythmia which is a general term that refers to an abnormal heart rhythm. The basis of arrh...
Neural Networks, Computer Databases, Factual Female Male Heart Rate Models, Cardiovascular Electrocardiography Myocardial Contraction Humans Signal Processing, Computer-Assisted Arrhythmias, Cardiac
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Discriminatively Trained Latent Ordinal Model for Video Classification.

IEEE transactions on pattern analysis and machine intelligence Aug 22, 2017
We address the problem of video classification for facial analysis and human action recognition. We propose a novel weakly supervised learning method that models the video as a sequence of automatically mined, discriminative sub-events (e.g., onset a...
Supervised Machine Learning Video Recording Pattern Recognition, Automated Algorithms Facial Expression Movement Databases, Factual Humans Stochastic Processes Artificial Intelligence Computer Graphics Models, Statistical Running
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Transfer Learning: A Riemannian Geometry Framework With Applications to Brain-Computer Interfaces.

IEEE transactions on bio-medical engineering Aug 21, 2017
OBJECTIVE: This paper tackles the problem of transfer learning in the context of electroencephalogram (EEG)-based brain-computer interface (BCI) classification. In particular, the problems of cross-session and cross-subject classification are conside...
Models, Theoretical Electroencephalography Brain-Computer Interfaces Humans Machine Learning Databases, Factual
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A neural network multi-task learning approach to biomedical named entity recognition.

BMC bioinformatics Aug 15, 2017
BACKGROUND: Named Entity Recognition (NER) is a key task in biomedical text mining. Accurate NER systems require task-specific, manually-annotated datasets, which are expensive to develop and thus limited in size. Since such datasets contain related ...
Neural Networks, Computer Machine Learning Databases, Factual Models, Theoretical Data Mining
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