AIMC Topic: Decision Trees

Clear Filters Showing 411 to 420 of 600 articles

A machine learning based framework to identify and classify long terminal repeat retrotransposons.

PLoS computational biology
Transposable elements (TEs) are repetitive nucleotide sequences that make up a large portion of eukaryotic genomes. They can move and duplicate within a genome, increasing genome size and contributing to genetic diversity within and across species. A...

Ensemble of Rotation Trees for Imbalanced Medical Datasets.

Journal of healthcare engineering
Medical datasets are often predominately composed of "normal" examples with only a small percentage of "abnormal" ones and how to correctly recognize the abnormal examples is very meaningful. However, conventional classification learning methods try ...

Identification of Migratory Insects from their Physical Features using a Decision-Tree Support Vector Machine and its Application to Radar Entomology.

Scientific reports
Migration is a key process in the population dynamics of numerous insect species, including many that are pests or vectors of disease. Identification of insect migrants is critically important to studies of insect migration. Radar is an effective mea...

Predication of different stages of Alzheimer's disease using neighborhood component analysis and ensemble decision tree.

Journal of neuroscience methods
BACKGROUND: There is a spectrum of the progression from healthy control (HC) to mild cognitive impairment (MCI) without conversion to Alzheimer's disease (AD), to MCI with conversion to AD (cMCI), and to AD. This study aims to predict the different d...

Predicting treatment outcome of drug-susceptible tuberculosis patients using machine-learning models.

Informatics for health & social care
Tuberculosis (TB) is a deadly contagious disease and a serious global health problem. It is curable but due to its lengthy treatment process, a patient is likely to leave the treatment incomplete, leading to a more lethal, drug resistant form of dise...

Mortality prediction in intensive care units (ICUs) using a deep rule-based fuzzy classifier.

Journal of biomedical informatics
Electronic health records (EHRs) contain critical information useful for clinical studies. Early assessment of patients' mortality in intensive care units is of great importance. In this paper, a Deep Rule-Based Fuzzy System (DRBFS) was proposed to d...

Predicting the Effect of Single and Multiple Mutations on Protein Structural Stability.

Molecules (Basel, Switzerland)
Predicting how a point mutation alters a protein's stability can guide pharmaceutical drug design initiatives which aim to counter the effects of serious diseases. Conducting mutagenesis studies in physical proteins can give insights about the effect...

Bayesian averaging over Decision Tree models for trauma severity scoring.

Artificial intelligence in medicine
Health care practitioners analyse possible risks of misleading decisions and need to estimate and quantify uncertainty in predictions. We have examined the "gold" standard of screening a patient's conditions for predicting survival probability, based...

Estimating causal effects for survival (time-to-event) outcomes by combining classification tree analysis and propensity score weighting.

Journal of evaluation in clinical practice
RATIONALE, AIMS AND OBJECTIVES: A common approach to assessing treatment effects in nonrandomized studies with time-to-event outcomes is to estimate propensity scores and compute weights using logistic regression, test for covariate balance, and then...