AIMC Topic: Decision Trees

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Ensemble of random forests One vs. Rest classifiers for MCI and AD prediction using ANOVA cortical and subcortical feature selection and partial least squares.

Journal of neuroscience methods Dec 11, 2017
BACKGROUND: Alzheimer's disease (AD) is the most common cause of dementia in the elderly and affects approximately 30 million individuals worldwide. Mild cognitive impairment (MCI) is very frequently a prodromal phase of AD, and existing studies have...
Humans Decision Trees Least-Squares Analysis Alzheimer Disease Image Interpretation, Computer-Assisted Pattern Recognition, Automated Analysis of Variance Machine Learning Databases, Factual Brain Female Aged Male Disease Progression Cognitive Dysfunction Magnetic Resonance Imaging
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A novel method for predicting kidney stone type using ensemble learning.

Artificial intelligence in medicine Dec 11, 2017
The high morbidity rate associated with kidney stone disease, which is a silent killer, is one of the main concerns in healthcare systems all over the world. Advanced data mining techniques such as classification can help in the early prediction of t...
Young Adult Adult Male Middle Aged Adolescent Databases, Factual Female Risk Factors Aged Aged, 80 and over Bayes Theorem Iran Data Mining Early Diagnosis Kidney Calculi Child, Preschool Child Decision Support Systems, Clinical Decision Trees Predictive Value of Tests Humans Neural Networks, Computer Machine Learning Decision Support Techniques
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Profiling Arthritis Pain with a Decision Tree.

Pain practice : the official journal of World Institute of Pain Nov 20, 2017
BACKGROUND: Arthritis is the leading cause of work disability and contributes to lost productivity. Previous studies showed that various factors predict pain, but they were limited in sample size and scope from a data analytics perspective.
Decision Trees Pain Data Mining Arthritis Humans Machine Learning Algorithms Sensitivity and Specificity
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Seeing the forest beyond the trees: Predicting survival in burn patients with machine learning.

American journal of surgery Nov 7, 2017
BACKGROUND: This study aims to identify predictors of survival for burn patients at the patient and hospital level using machine learning techniques.
Infant Hospitals Adolescent Child, Preschool Child United States Decision Trees Burns Aged, 80 and over Young Adult Adult Male Middle Aged Clinical Decision-Making Female Infant, Newborn Aged Humans Machine Learning Decision Support Techniques Prognosis
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Identifying causal mechanisms in health care interventions using classification tree analysis.

Journal of evaluation in clinical practice Nov 3, 2017
RATIONALE, AIMS, AND OBJECTIVES: Mediation analysis identifies causal pathways by testing the relationships between the treatment, the outcome, and an intermediate variable that mediates the relationship between the treatment and outcome. This paper ...
Age Factors Models, Statistical Decision Trees Sex Factors Employment Female Adult Male Middle Aged Depression Outcome and Process Assessment, Health Care Humans Machine Learning
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Supervised learning techniques and their ability to classify a change of direction task strategy using kinematic and kinetic features.

Journal of biomechanics Oct 31, 2017
This study examines the ability of commonly used supervised learning techniques to classify the execution of a maximum effort change of direction task into predefined movement pattern as well as the influence of fuzzy executions and the impact of sel...
Ankle Hip Joint Ankle Joint Sports Movement Humans Young Adult Decision Trees Bayes Theorem Discriminant Analysis Rotation Range of Motion, Articular Adult Biomechanical Phenomena Male Support Vector Machine Models, Statistical
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Machine learning applied to neuroimaging for diagnosis of adult classic Chiari malformation: role of the basion as a key morphometric indicator.

Journal of neurosurgery Oct 20, 2017
OBJECTIVE The current diagnostic criterion for Chiari malformation Type I (CM-I), based on tonsillar herniation (TH), includes a diversity of patients with amygdalar descent that may be caused by a variety of factors. In contrast, patients presenting...
Decision Trees Diagnosis, Differential Cephalometry Neuroimaging Arnold-Chiari Malformation Skull Base Amygdala Encephalocele Foramen Magnum Humans Machine Learning Adult Logistic Models
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Learning ensemble classifiers for diabetic retinopathy assessment.

Artificial intelligence in medicine Oct 6, 2017
Diabetic retinopathy is one of the most common comorbidities of diabetes. Unfortunately, the recommended annual screening of the eye fundus of diabetic patients is too resource-consuming. Therefore, it is necessary to develop tools that may help doct...
Humans Decision Support Systems, Clinical Diabetes Mellitus, Type 2 Diabetes Mellitus, Type 1 Fuzzy Logic Decision Trees Predictive Value of Tests Clinical Decision-Making Reproducibility of Results Diabetic Retinopathy Risk Factors Machine Learning Risk Assessment Decision Support Techniques Time Factors Prognosis Electronic Health Records
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Fuzzy-Rough Cognitive Networks.

Neural networks : the official journal of the International Neural Network Society Sep 28, 2017
Rough Cognitive Networks (RCNs) are a kind of granular neural network that augments the reasoning rule present in Fuzzy Cognitive Maps with crisp information granules coming from Rough Set Theory. While RCNs have shown promise in solving different cl...
Pattern Recognition, Automated Problem Solving Discrimination, Psychological Models, Theoretical Fuzzy Logic Neural Networks, Computer Decision Trees Algorithms Bayes Theorem Computer Simulation Benchmarking Cognition
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Single Nucleotide Polymorphism relevance learning with Random Forests for Type 2 diabetes risk prediction.

Artificial intelligence in medicine Sep 22, 2017
OBJECTIVE: The use of artificial intelligence techniques to find out which Single Nucleotide Polymorphisms (SNPs) promote the development of a disease is one of the features of medical research, as such techniques may potentially aid early diagnosis ...
Logistic Models Humans Support Vector Machine Decision Support Systems, Clinical Decision Support Techniques Phenotype Prognosis Clinical Decision-Making Risk Factors Risk Assessment Decision Trees Diabetes Mellitus, Type 2 Genetic Predisposition to Disease Polymorphism, Single Nucleotide
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