AIMC Topic: Pattern Recognition, Automated

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Breast cancer detection and classification in digital mammography based on Non-Subsampled Contourlet Transform (NSCT) and Super Resolution.

Computer methods and programs in biomedicine Jul 4, 2015
Breast cancer is one of the most perilous diseases among women. Breast screening is a method of detecting breast cancer at a very early stage which can reduce the mortality rate. Mammography is a standard method for the early diagnosis of breast canc...
Mammography Sample Size Signal Processing, Computer-Assisted Pattern Recognition, Automated Female Humans Machine Learning Radiographic Image Enhancement Reproducibility of Results Algorithms Sensitivity and Specificity Breast Neoplasms Fuzzy Logic
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NLP based congestive heart failure case finding: A prospective analysis on statewide electronic medical records.

International journal of medical informatics Jul 2, 2015
BACKGROUND: In order to proactively manage congestive heart failure (CHF) patients, an effective CHF case finding algorithm is required to process both structured and unstructured electronic medical records (EMR) to allow complementary and cost-effic...
Humans Algorithms Prospective Studies Electronic Health Records Natural Language Processing Heart Failure Data Mining Pattern Recognition, Automated Vocabulary, Controlled Reproducibility of Results Sensitivity and Specificity Prevalence Decision Support Systems, Clinical Maine
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Combining glass box and black box evaluations in the identification of heart disease risk factors and their temporal relations from clinical records.

Journal of biomedical informatics Jul 2, 2015
BACKGROUND: The determination of risk factors and their temporal relations in natural language patient records is a complex task which has been addressed in the i2b2/UTHealth 2014 shared task. In this context, in most systems it was broadly decompose...
Risk Assessment Comorbidity Incidence Cohort Studies Longitudinal Studies Aged Male Cardiovascular Diseases Middle Aged Pattern Recognition, Automated France Computer Security Vocabulary, Controlled Diabetes Complications Narration Natural Language Processing Confidentiality Data Mining Humans Algorithms Electronic Health Records Female
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LogDet Rank Minimization with Application to Subspace Clustering.

Computational intelligence and neuroscience Jul 2, 2015
Low-rank matrix is desired in many machine learning and computer vision problems. Most of the recent studies use the nuclear norm as a convex surrogate of the rank operator. However, all singular values are simply added together by the nuclear norm, ...
Image Interpretation, Computer-Assisted Pattern Recognition, Automated Machine Learning Algorithms Cluster Analysis Data Interpretation, Statistical
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Using local lexicalized rules to identify heart disease risk factors in clinical notes.

Journal of biomedical informatics Jun 29, 2015
Heart disease is the leading cause of death globally and a significant part of the human population lives with it. A number of risk factors have been recognized as contributing to the disease, including obesity, coronary artery disease (CAD), hyperte...
Vocabulary, Controlled Diabetes Complications United Kingdom Semantics Pattern Recognition, Automated Computer Security Narration Humans Natural Language Processing Electronic Health Records Confidentiality Female Data Mining Risk Assessment Aged Comorbidity Male Incidence Cardiovascular Diseases Cohort Studies Middle Aged Longitudinal Studies
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Designing Artificial Neural Networks Using Particle Swarm Optimization Algorithms.

Computational intelligence and neuroscience Jun 29, 2015
Artificial Neural Network (ANN) design is a complex task because its performance depends on the architecture, the selected transfer function, and the learning algorithm used to train the set of synaptic weights. In this paper we present a methodology...
Neurons Neural Networks, Computer Pattern Recognition, Automated Algorithms Chromosome Pairing
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The role of fine-grained annotations in supervised recognition of risk factors for heart disease from EHRs.

Journal of biomedical informatics Jun 26, 2015
This paper describes a supervised machine learning approach for identifying heart disease risk factors in clinical text, and assessing the impact of annotation granularity and quality on the system's ability to recognize these risk factors. We utiliz...
Humans Electronic Health Records Female Aged Male Middle Aged Risk Assessment Data Mining Narration Comorbidity Pattern Recognition, Automated Diabetes Complications Natural Language Processing Incidence Computer Security Maryland Coronary Artery Disease Vocabulary, Controlled Cohort Studies Confidentiality Longitudinal Studies Supervised Machine Learning
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Automatic de-identification of electronic medical records using token-level and character-level conditional random fields.

Journal of biomedical informatics Jun 26, 2015
De-identification, identifying and removing all protected health information (PHI) present in clinical data including electronic medical records (EMRs), is a critical step in making clinical data publicly available. The 2014 i2b2 (Center of Informati...
Data Mining Pattern Recognition, Automated Computer Security Narration Electronic Health Records Vocabulary, Controlled Natural Language Processing China Data Interpretation, Statistical Cohort Studies Confidentiality
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Lumbar Ultrasound Image Feature Extraction and Classification with Support Vector Machine.

Ultrasound in medicine & biology Jun 26, 2015
Needle entry site localization remains a challenge for procedures that involve lumbar puncture, for example, epidural anesthesia. To solve the problem, we have developed an image classification algorithm that can automatically identify the bone/inter...
Anesthesia, Epidural Punctures Image Interpretation, Computer-Assisted Pattern Recognition, Automated Image Enhancement Humans Algorithms Pregnancy Female Reproducibility of Results Sensitivity and Specificity Support Vector Machine Ultrasonography, Interventional Lumbar Vertebrae
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Interpreting support vector machine models for multivariate group wise analysis in neuroimaging.

Medical image analysis Jun 25, 2015
Machine learning based classification algorithms like support vector machines (SVMs) have shown great promise for turning a high dimensional neuroimaging data into clinically useful decision criteria. However, tracing imaging based patterns that cont...
Image Enhancement Multivariate Analysis Magnetic Resonance Imaging Humans Models, Statistical Brain Pattern Recognition, Automated Computer Simulation Neuroimaging Reproducibility of Results Sensitivity and Specificity Support Vector Machine
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