AIMC Topic: Data Mining

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Budget constrained non-monotonic feature selection.

Neural networks : the official journal of the International Neural Network Society Sep 4, 2015
Feature selection is an important problem in machine learning and data mining. We consider the problem of selecting features under the budget constraint on the feature subset size. Traditional feature selection methods suffer from the "monotonic" pro...
Computer Simulation Benchmarking Fires Data Mining Housing Artificial Intelligence Machine Learning Algorithms Databases, Factual
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Coronary artery disease risk assessment from unstructured electronic health records using text mining.

Journal of biomedical informatics Aug 28, 2015
Coronary artery disease (CAD) often leads to myocardial infarction, which may be fatal. Risk factors can be used to predict CAD, which may subsequently lead to prevention or early intervention. Patient data such as co-morbidities, medication history,...
Computer Security Vocabulary, Controlled Female Diabetes Complications Narration Aged Humans New South Wales Risk Assessment Natural Language Processing Electronic Health Records Male Comorbidity Confidentiality Cardiovascular Diseases Incidence Data Mining Middle Aged Cohort Studies Pattern Recognition, Automated Longitudinal Studies
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Annotating longitudinal clinical narratives for de-identification: The 2014 i2b2/UTHealth corpus.

Journal of biomedical informatics Aug 28, 2015
The 2014 i2b2/UTHealth natural language processing shared task featured a track focused on the de-identification of longitudinal medical records. For this track, we de-identified a set of 1304 longitudinal medical records describing 296 patients. Thi...
Electronic Health Records Documentation Cohort Studies Pattern Recognition, Automated Computer Security Narration Vocabulary, Controlled Natural Language Processing Confidentiality Data Mining
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Adapting existing natural language processing resources for cardiovascular risk factors identification in clinical notes.

Journal of biomedical informatics Aug 28, 2015
The 2014 i2b2 natural language processing shared task focused on identifying cardiovascular risk factors such as high blood pressure, high cholesterol levels, obesity and smoking status among other factors found in health records of diabetic patients...
Longitudinal Studies Narration Natural Language Processing Confidentiality Data Mining Utah Pattern Recognition, Automated Computer Security Vocabulary, Controlled Diabetes Complications Middle Aged Risk Assessment Comorbidity Incidence Cohort Studies Electronic Health Records Humans Female Aged Male Cardiovascular Diseases
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CRFs based de-identification of medical records.

Journal of biomedical informatics Aug 24, 2015
De-identification is a shared task of the 2014 i2b2/UTHealth challenge. The purpose of this task is to remove protected health information (PHI) from medical records. In this paper, we propose a novel de-identifier, WI-deId, based on conditional rand...
Vocabulary, Controlled Data Interpretation, Statistical Electronic Health Records Confidentiality China Data Mining Cohort Studies Pattern Recognition, Automated Narration Computer Security Natural Language Processing
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Mining heart disease risk factors in clinical text with named entity recognition and distributional semantic models.

Journal of biomedical informatics Aug 21, 2015
We present the design, and analyze the performance of a multi-stage natural language processing system employing named entity recognition, Bayesian statistics, and rule logic to identify and characterize heart disease risk factor events in diabetic p...
Pattern Recognition, Automated Computer Security Vocabulary, Controlled Diabetes Complications Wisconsin Humans Narration Electronic Health Records Natural Language Processing Female Confidentiality Aged Incidence Data Mining Semantics Male Cohort Studies Cardiovascular Diseases Longitudinal Studies Middle Aged Models, Statistical Risk Assessment Comorbidity
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Classification of Medical Datasets Using SVMs with Hybrid Evolutionary Algorithms Based on Endocrine-Based Particle Swarm Optimization and Artificial Bee Colony Algorithms.

Journal of medical systems Aug 20, 2015
The classification and analysis of data is an important issue in today's research. Selecting a suitable set of features makes it possible to classify an enormous quantity of data quickly and efficiently. Feature selection is generally viewed as a pro...
Humans Artificial Intelligence Algorithms Support Vector Machine Data Mining
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Risk factor detection for heart disease by applying text analytics in electronic medical records.

Journal of biomedical informatics Aug 14, 2015
In the United States, about 600,000 people die of heart disease every year. The annual cost of care services, medications, and lost productivity reportedly exceeds 108.9 billion dollars. Effective disease risk assessment is critical to prevention, ca...
Cardiovascular Diseases Middle Aged Risk Assessment Comorbidity Incidence Humans Electronic Health Records Female Aged Male Data Mining Pattern Recognition, Automated California Computer Security Vocabulary, Controlled Cohort Studies Longitudinal Studies Narration Natural Language Processing Confidentiality Diabetes Complications
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jEcho: an Evolved weight vector to CHaracterize the protein's posttranslational modification mOtifs.

Interdisciplinary sciences, computational life sciences Aug 6, 2015
Protein's posttranslational modification (PTM) represents a major dynamic regulation of protein functions after the translation of polypeptide chains from mRNA molecule. Compared with the costly and labor-intensive wet laboratory characterization of ...
Support Vector Machine Data Mining Protein Processing, Post-Translational Databases, Protein Software Design Phosphorylation Amino Acid Motifs
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Prediction of Allogeneic Hematopoietic Stem-Cell Transplantation Mortality 100 Days After Transplantation Using a Machine Learning Algorithm: A European Group for Blood and Marrow Transplantation Acute Leukemia Working Party Retrospective Data Mining Study.

Journal of clinical oncology : official journal of the American Society of Clinical Oncology Aug 3, 2015
PURPOSE: Allogeneic hematopoietic stem-cell transplantation (HSCT) is potentially curative for acute leukemia (AL), but carries considerable risk. Machine learning algorithms, which are part of the data mining (DM) approach, may serve for transplanta...
Disease-Free Survival Data Mining Hematopoietic Stem Cell Transplantation Transplantation, Homologous Precursor Cell Lymphoblastic Leukemia-Lymphoma Europe Leukemia, Myeloid, Acute Decision Trees Male Kaplan-Meier Estimate Predictive Value of Tests Middle Aged Area Under Curve Retrospective Studies Risk Assessment Registries Humans Postoperative Complications Female Machine Learning Reproducibility of Results Disease Progression Algorithms Risk Factors Time Factors Decision Support Techniques Adult ROC Curve Logistic Models Treatment Outcome
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