AI Medical Compendium Topic:
Decision Trees

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Cardiovascular Dysautonomias Diagnosis Using Crisp and Fuzzy Decision Tree: A Comparative Study.

Studies in health technology and informatics Jan 1, 2016
Decision trees (DTs) are one of the most popular techniques for learning classification systems, especially when it comes to learning from discrete examples. In real world, many data occurred in a fuzzy form. Hence a DT must be able to deal with such...
Decision Support Techniques Cardiovascular Diseases Fuzzy Logic Humans Algorithms Autonomic Nervous System Primary Dysautonomias Decision Trees Blood Pressure Heart Rate
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Evaluation of Machine Learning Algorithm Utilization for Lung Cancer Classification Based on Gene Expression Levels.

Asian Pacific journal of cancer prevention : APJCP Jan 1, 2016
BACKGROUND: Lung cancer remains one of the most common cancers in the world, both in terms of new cases (about 13% of total per year) and deaths (nearly one cancer death in five), because of the high case fatality. Errors in lung cancer type or malig...
Humans Small Cell Lung Carcinoma Gene Expression Profiling Databases, Factual Case-Control Studies Carcinoma, Squamous Cell Machine Learning Lung Neoplasms Biomarkers, Tumor Algorithms Adenocarcinoma Support Vector Machine Decision Trees
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Use of machine learning approaches for novel drug discovery.

Expert opinion on drug discovery Jan 1, 2016
INTRODUCTION: The use of computational tools in the early stages of drug development has increased in recent decades. Machine learning (ML) approaches have been of special interest, since they can be applied in several steps of the drug discovery met...
Machine Learning Molecular Docking Simulation Drug Design Humans Neural Networks, Computer Models, Biological Ligands Drug Discovery Binding Sites Support Vector Machine Decision Trees
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Using Time Series Analysis to Predict Cardiac Arrest in a PICU.

Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies Nov 1, 2015
OBJECTIVES: To build and test cardiac arrest prediction models in a PICU, using time series analysis as input, and to measure changes in prediction accuracy attributable to different classes of time series data.
Heart Arrest Support Vector Machine Decision Trees Predictive Value of Tests Area Under Curve Linear Models Multivariate Analysis Child Intensive Care Units, Pediatric ROC Curve Adolescent Child, Preschool Humans Neural Networks, Computer Retrospective Studies Young Adult Infant
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An Efficient Approach for Automated Mass Segmentation and Classification in Mammograms.

Journal of digital imaging Oct 1, 2015
Breast cancer is becoming a leading death of women all over the world; clinical experiments demonstrate that early detection and accurate diagnosis can increase the potential of treatment. In order to improve the breast cancer diagnosis precision, th...
Humans Algorithms Databases, Factual Female Image Interpretation, Computer-Assisted Support Vector Machine Decision Trees Mammography Reproducibility of Results Sensitivity and Specificity Breast Neoplasms
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Towards a predictive model for Guillain-Barré syndrome.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Aug 1, 2015
The severity of Guillain-Barré Syndrome (GBS) varies among subtypes, which can be mainly Acute Inflammatory Demyelinating Polyneuropathy (AIDP), Acute Motor Axonal Neuropathy (AMAN), Acute Motor Sensory Axonal Neuropathy (AMSAN) and Miller-Fisher Syn...
Forecasting Support Vector Machine Decision Trees Humans Neurologic Examination Serologic Tests Neural Conduction Guillain-Barre Syndrome
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Improving medical diagnosis reliability using Boosted C5.0 decision tree empowered by Particle Swarm Optimization.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Aug 1, 2015
Improving accuracy of supervised classification algorithms in biomedical applications is one of active area of research. In this study, we improve the performance of Particle Swarm Optimization (PSO) combined with C4.5 decision tree (PSO+C4.5) classi...
Decision Trees Diagnostic Techniques and Procedures Female Humans Reproducibility of Results Machine Learning Sensitivity and Specificity Algorithms Databases, Factual
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Diagnosis of periodontal diseases using different classification algorithms: a preliminary study.

Nigerian journal of clinical practice Jan 1, 2015
OBJECTIVE: The purpose of the proposed study was to develop an identification unit for classifying periodontal diseases using support vector machine (SVM), decision tree (DT), and artificial neural networks (ANNs).
Radiography Periodontal Diseases Male Middle Aged Adolescent Risk Factors Support Vector Machine Young Adult Decision Trees Adult Humans Diagnosis, Computer-Assisted Female
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