An evidential reasoning rule based feature selection for improving trauma outcome prediction

A Machine Learning–Based Model to Predict Acute Traumatic Coagulopathy in Trauma Patients Upon Emergency Hospitalization

(2020) Kaiyuan Li et al.   CLINICAL AND APPLIED THROMBOSIS-HEMOSTASIS

Improving Prediction of Favourable Outcome After 6 Months in Patients with Severe Traumatic Brain Injury Using Physiological Cerebral Parameters in a Multivariable Logistic Regression Model

(2020) Frank C. Bennis et al.   Neurocritical Care

Investigation of Machine Learning Approaches for Traumatic Brain Injury Classification via EEG Assessment in Mice

(2020) Manoj Vishwanath et al.   SENSORS

Performance comparison of linear and non-linear feature selection methods for the analysis of large survey datasets

(2019) Olga Krakovska et al.   PLoS One

Hybrid Particle Swarm Optimization with Spiral-Shaped Mechanism for Feature Selection

(2019) Ke Chen et al.   EXPERT SYSTEMS WITH APPLICATIONS

Machine Learning to Predict In-hospital Morbidity and Mortality after Traumatic Brain Injury

(2019) Kazuya Matsuo et al.   JOURNAL OF NEUROTRAUMA

Identifying incidental findings from radiology reports of trauma patients: An evaluation of automated feature representation methods

(2019) Gaurav Trivedi et al.   INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS

Random Forest Modeling Can Predict Infectious Complications Following Trauma Laparotomy

(2019) Rondi B. Gelbard et al.   Journal of Trauma and Acute Care Surgery

Development of an EMG-Based Muscle Health Model for Elbow Trauma Patients

(2019) Emma Farago et al.   SENSORS

A Framework for Automatic Morphological Feature Extraction and Analysis of Abdominal Organs in MRI Volumes

(2019) Hykoush Asaturyan et al.   JOURNAL OF MEDICAL SYSTEMS

Feature selection for high dimensional imbalanced class data using harmony search

(2017) Alireza Moayedikia et al.   ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

Multiclassifier Systems for Predicting Neurological Outcome of Patients with Severe Trauma and Polytrauma in Intensive Care Units

(2017) Javier González-Robledo et al.   JOURNAL OF MEDICAL SYSTEMS

Data classification using evidence reasoning rule

(2017) Xiaobin Xu et al.   KNOWLEDGE-BASED SYSTEMS

Ensemble feature selection: Homogeneous and heterogeneous approaches

(2017) B. Seijo-Pardo et al.   KNOWLEDGE-BASED SYSTEMS

Missing data and multiple imputation in clinical epidemiological research

(2017) Alma Pedersen et al.   Clinical Epidemiology

Random forests and evidential belief function-based landslide susceptibility assessment in Western Mazandaran Province, Iran

(2016) Hamid Reza Pourghasemi et al.   Environmental Earth Sciences

A tutorial on variable selection for clinical prediction models: feature selection methods in data mining could improve the results

(2016) Farideh Bagherzadeh-Khiabani et al.   JOURNAL OF CLINICAL EPIDEMIOLOGY

Belief rule-based inference for predicting trauma outcome

(2016) Guilan Kong et al.   KNOWLEDGE-BASED SYSTEMS

Predictors of Outcome in Traumatic Brain Injury: New Insight Using Receiver Operating Curve Indices and Bayesian Network Analysis

(2016) Zsolt Zador et al.   PLoS One

Dealing with the evaluation of supervised classification algorithms

(2015) Guzman Santafe et al.   ARTIFICIAL INTELLIGENCE REVIEW

Mortality risk prediction in burn injury: Comparison of logistic regression with machine learning approaches

(2015) Neophytos Stylianou et al.   BURNS

Prediction modelling for trauma using comorbidity and ‘true’ 30-day outcome

(2015) Omar Bouamra et al.   EMERGENCY MEDICINE JOURNAL

Evaluating multiple classifiers for stock price direction prediction

(2015) Michel Ballings et al.   EXPERT SYSTEMS WITH APPLICATIONS

Recent advances and emerging challenges of feature selection in the context of big data

(2015) V. Bolón-Canedo et al.   KNOWLEDGE-BASED SYSTEMS

Knowledge discovery in medicine: Current issue and future trend

(2014) Nura Esfandiari et al.   EXPERT SYSTEMS WITH APPLICATIONS

Feature selection for high-dimensional class-imbalanced data sets using Support Vector Machines

(2014) Sebastián Maldonado et al.   INFORMATION SCIENCES

Spatial Attention Does Not Modulate Holistic Face Processing, Even When Multiple Faces are Present

(2014) Liam J Norman et al.   PERCEPTION

Importance of sample size, data type and prediction method for remote sensing-based estimations of aboveground forest biomass

(2014) F.E. Fassnacht et al.   REMOTE SENSING OF ENVIRONMENT

Merits of random forests emerge in evaluation of chemometric classifiers by external validation

(2013) I.M. Scott et al.   ANALYTICA CHIMICA ACTA

Evidential reasoning rule for evidence combination

(2013) Jian-Bo Yang et al.   ARTIFICIAL INTELLIGENCE

Spectral Discrimination of Insect Defoliation Levels in Mopane Woodland Using Hyperspectral Data

(2013) Samuel Adelabu et al.   IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

Feature selection for high-dimensional imbalanced data

(2012) Liuzhi Yin et al.   NEUROCOMPUTING

Quantifying aboveground forest carbon pools and fluxes from repeat LiDAR surveys

(2012) Andrew T. Hudak et al.   REMOTE SENSING OF ENVIRONMENT

An introduction and survey of the evidential reasoning approach for multiple criteria decision analysis

(2011) Dong-Ling Xu   ANNALS OF OPERATIONS RESEARCH

Data-mining-based dynamic dispatching rule selection mechanism for shop floor control systems using a support vector machine approach

(2008) Yeou-Ren Shiue   INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH