Probability estimation with machine learning methods for dichotomous and multicategory outcome: Applications

No abstract is available for this paper.

• Publication year

  2014

• Venue

  Biometrical journal. Biometrische Zeitschrift

• Publication date

  2014-07-01

• Fields of study

  Medicine, Computer Science

• Identifiers
  DOI 10.1002/bimj.201300077PMID 24989843
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

• FUNCTIONAL EVALUATION: THE BARTHEL INDEX.

  2018cited by this paper
• A note on the evaluation of novel biomarkers: do not rely on integrated discrimination improvement and net reclassification index

  2014cited by this paper
• Probability estimation with machine learning methods for dichotomous and multicategory outcome: Theory

  2014influential reference
• Statistical Learning for Biomedical Data

  2013cited by this paper
• Difference of two dependent sensitivities and specificities: Comparison of various approaches

  2013cited by this paper
• Consumer credit risk: Individual probability estimates using machine learning

  2013cited by this paper
• Risk estimation and risk prediction using machine-learning methods

  2012cited by this paper
• Identifying representative trees from ensembles

  2012cited by this paper
• Overview of random forest methodology and practical guidance with emphasis on computational biology and bioinformatics

  2012cited by this paper
• Bidirectional discrimination with application to data visualization.

  2012cited by this paper
• Optimal weighted nearest neighbour classifiers

  2011cited by this paper
• Probability Machines

  2011cited by this paper
• A clinical prediction rule for the diagnosis of coronary artery disease: validation, updating, and extension.

  2011cited by this paper
• [Regression modeling strategies].

  2011cited by this paper
• The behaviour of random forest permutation-based variable importance measures under predictor correlation

  2010cited by this paper
• On safari to Random Jungle: a fast implementation of Random Forests for high-dimensional data

  2010cited by this paper
• Multivariable model‐building: A pragmatic approach to regression analysis based on fractional polynomials for modelling continuous variables. Patrick Royston and Willi Sauerbrei, Wiley, Chichester, 2008. No. of pages: 322. Price: $130.00. ISBN: 978‐0‐470‐02842‐1

  2009cited by this paper
• On Graphically Checking Goodness-of-fit of Binary Logistic Regression Models

  2009cited by this paper
• Sampling Uncertainty and Confidence Intervals for the Brier Score and Brier Skill Score

  2008cited by this paper
• Probability estimation for large-margin classifiers

  2008cited by this paper
• Multivariable Model-Building: A Pragmatic Approach to Regression Analysis based on Fractional Polynomials for Modelling Continuous Variables

  2008cited by this paper
• Patient-centered yes/no prognosis using learning machines

  2008cited by this paper
• Practical experiences on the necessity of external validation

  2007cited by this paper
• Comparing Probabilistic Forecasting Systems with the Brier Score

  2007cited by this paper
• A supplement to: "A new confidence interval for the difference between two binomial proportions of paired data"

  2007cited by this paper
• A comparison of PSO and GA approaches for gene selection and classification of microarray data

  2007cited by this paper
• Strictly Proper Scoring Rules, Prediction, and Estimation

  2007cited by this paper
• The discrete brier and ranked probability skill scores

  2007cited by this paper
• EGFR Activation and Ultraviolet Light-Induced Skin Carcinogenesis

  2006cited by this paper
• Support Vector Machines with Applications

  2006cited by this paper
• Support Vector Machines in R

  2006cited by this paper
• A new confidence interval for the difference between two binomial proportions of paired data

  2005cited by this paper
• Prognostic/Clinical Prediction Models: Multivariable Prognostic Models: Issues in Developing Models, Evaluating Assumptions and Adequacy, and Measuring and Reducing Errors

  2005cited by this paper
• Properties of bagged nearest neighbour classifiers

  2005cited by this paper
• Nearest neighbor ensemble

  2004cited by this paper
• New Intervals for the Difference Between Two Independent Binomial Proportions

  2004cited by this paper
• Confidence Intervals for the Area Under the ROC Curve

  2004cited by this paper
• A simple alternative confidence interval for the difference between two proportions.

  2004cited by this paper
• Age and National Institutes of Health Stroke Scale Score Within 6 Hours After Onset Are Accurate Predictors of Outcome After Cerebral Ischemia: Development and External Validation of Prognostic Models

  2003cited by this paper
• Support Vector Machines and the Bayes Rule in Classification

  2002cited by this paper
• Predicting functional outcome and survival after acute ischemic stroke

  2002cited by this paper
• Regression Modeling Strategies: With Applications to Linear Models, Logistic Regression, and Survival Analysis

  2001cited by this paper
• Learning with Kernels: support vector machines, regularization, optimization, and beyond

  2001cited by this paper
• Application of Resampling Techniques to the Statistical Analysis of the Brier Score

  2001cited by this paper
• Information Theoretic Feature Crediting in Multiclass Support Vector Machines

  2001cited by this paper
• Confidence intervals for differences in correlated binary proportions.

  2000cited by this paper
• Confidence intervals for differnces in correlated binary proportions by W. L. May and W. D. Johnson, Statistics in Medicine, 16, 2127–2136 (1997)

  2000cited by this paper
• Improved confidence intervals for the difference between binomial proportions based on paired data.

  1998cited by this paper
• Interval estimation for the difference between independent proportions: comparison of eleven methods.

  1998cited by this paper
• Two-sided confidence intervals for the single proportion: comparison of seven methods.

  1998cited by this paper
• Confidence intervals for differences in correlated binary proportions.

  1997cited by this paper
• Efficiency of reduced logistic regression models

  1994cited by this paper
• Assessing predictive accuracy: how to compare Brier scores.

  1991cited by this paper
• Applications of Expert Systems

  1989cited by this paper
• International application of a new probability algorithm for the diagnosis of coronary artery disease.

  1989cited by this paper
• Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach.

  1988influential reference
• Inductive knowledge acquisition: a case study

  1987cited by this paper
• Probabilistic prediction in patient management and clinical trials.

  1986cited by this paper
• Statistical inference for Pr(Y < X): The normal case

  1986influential reference
• Bayesian probability analysis: a prospective demonstration of its clinical utility in diagnosing coronary disease.

  1984cited by this paper
• Calculation of polychotomous logistic regression parameters using individualized regressions

  1984cited by this paper
• Confidence intervals for the ratio of two binomial proportions

  1984cited by this paper
• VERIFICATION OF FORECASTS EXPRESSED IN TERMS OF PROBABILITY

  1950cited by this paper

• Ridehailing drivers’ perceptions and adoption of electric vehicles: Insights from a stratified random sample survey

  2026cites this paper
• Chronic Kidney Disease Prediction Model Based on Multiple Machine Learning Algorithms

  2025cites this paper
• Trustworthy Disentangled Framework for Multi-Label Medical Image Classification with Multimodal Refinement

  2025cites this paper
• Machine learning for credit risk management through cross-economy evidence in default prediction

  2025cites this paper
• Glioblastoma cancer: comparing the effectiveness of 3D conformal radiation therapy and volumetric modulated radiotherapy - an artificial intelligence-based survival prediction

  2025cites this paper
• Evaluation of approaches to internal validation of multinomial Logit models: The case of personal travel mode choice

  2025cites this paper
• Artificial Intelligence for Clinical Trial Facilitation, Lessons for Inflammatory Bowel Disease: A Scoping Review.

  2025cites this paper
• Subtypes of primary angle closure disease based on age-independent anterior segment optical coherence tomography parameters

  2025cites this paper
• Towards a holistic assessment of landslide susceptibility models: insights from the Central Eastern Alps

  2025cites this paper
• Age prediction from 12-lead electrocardiograms using deep learning: a comparison of four models on a contemporary, freely available dataset

  2024cites this paper
• Identification of putative coral pathogens in endangered Caribbean staghorn coral using machine learning.

  2024cites this paper
• AI in interventional cardiology: Innovations and challenges

  2024cites this paper
• The Artificial Intelligence Revolution in Stroke Care: A Decade of Scientific Evidence in Review.

  2024cites this paper
• How to develop, validate, and update clinical prediction models using multinomial logistic regression.

  2023cites this paper
• An Ontology for Reasoning About Fairness in Regression and Machine Learning

  2023cites this paper
• Calibrating machine learning approaches for probability estimation: A comprehensive comparison

  2023cites this paper
• Peer Prediction for Peer Review: Designing a Marketplace for Ideas

  2023cites this paper
• Necessity and Importance of Developing AI in Anesthesia from the Perspective of Clinical Safety and Information Security

  2023cites this paper
• Is My Driver Observation Model Overconfident? Input-Guided Calibration Networks for Reliable and Interpretable Confidence Estimates

  2022cites this paper
• Toward a Robust, Impact‐Based, Predictive Drought Metric

  2022cites this paper
• Differentiation of benign from malignant solid renal lesions using CT-based radiomics and machine learning: comparison with radiologist interpretation

  2022cites this paper
• Value of machine learning algorithms for predicting diabetes risk: A subset analysis from a real‐world retrospective cohort study

  2022cites this paper
• Stroke mortality prediction based on ensemble learning and the combination of structured and textual data

  2022cites this paper
• Spatial performance analysis in basketball with CART, random forest and extremely randomized trees

  2022cites this paper
• The Translational Machine: A novel machine‐learning approach to illuminate complex genetic architectures

  2021cites this paper
• Predicting Physician Consultations for Low Back Pain Using Claims Data and Population-Based Cohort Data—An Interpretable Machine Learning Approach

  2021influential citation
• Hypervolume under ROC manifold for discrete biomarkers with ties

  2021cites this paper
• Predicting short and long-term mortality after acute ischemic stroke using EHR.

  2021cites this paper
• Logistic regression was as good as machine learning for predicting major chronic diseases.

  2020cites this paper
• Comparison of complex modeling strategies for prediction of a binary outcome based on a few, highly correlated predictors

  2020cites this paper
• A signature enrichment design with Bayesian adaptive randomization

  2020cites this paper
• Comparison study of two-step LGD estimation model with probability machines

  2020influential citation
• Development of an absolute assignment predictor for triple-negative breast cancer subtyping using machine learning approaches

  2020cites this paper
• A systematic review of machine learning models for predicting outcomes of stroke with structured data

  2020influential citation
• Machine Learning to Predict Neonatal Mortality Using Public Health Data from Sao Paulo - Brazil

  2020cites this paper
• Developing clinical prediction models for diabetes classification and progression

  2020cites this paper
• Machine learning workflows to estimate class probabilities for precision cancer diagnostics on DNA methylation microarray data

  2020cites this paper
• Two‐sample test based on classification probability

  2019cites this paper
• Comparison of Machine Learning Techniques for Prediction of Hospitalization in Heart Failure Patients

  2019cites this paper
• A SIGNATURE ENRICHMENT DESIGN WITH BAYESIAN ADAPTIVE RANDOMIZATION FOR CANCER CLINICAL TRIALS

  2019cites this paper
• Survey of computational intelligence as basis to big flood management: challenges, research directions and future work

  2018influential citation
• Optimising the FIT: risk adjusted colorectal cancer screening using routine data

  2018influential citation
• Supervised Machine-learning Predictive Analytics for Prediction of Postinduction Hypotension

  2018cites this paper
• Making complex prediction rules applicable for readers: Current practice in random forest literature and recommendations

  2018cites this paper
• Simulation of complex data structures for planning of studies with focus on biomarker comparison

  2017cites this paper
• Efficiency of different measures for defining the applicability domain of classification models

  2017cites this paper
• On the application of statistical learning approaches to construct inverse probability weights in marginal structural Cox models: Hedging against weight-model misspecification

  2017cites this paper
• What is precision medicine?

  2017cites this paper
• An Ensemble of Optimal Trees for Class Membership Probability Estimation

  2016cites this paper
• Standardization of textual data for comprehensive job market analysis

  2016cites this paper
• Ensemble of a subset of kNN classifiers

  2016cites this paper
• A New method for Predicting Early-stage Lung nodules based on PSO-SVM Hybrid Algorithm

  2016cites this paper
• Ensemble of Subset of k-Nearest Neighbours Models for Class Membership Probability Estimation

  2016cites this paper
• Machine learning and data mining in complex genomic data—a review on the lessons learned in Genetic Analysis Workshop 19

  2016cites this paper
• A random forest guided tour

  2015cites this paper
• From a Ranking System to a Confidence Aware Semi-automatic Classifier

  2015cites this paper
• ranger: A Fast Implementation of Random Forests for High Dimensional Data in C++ and R

  2015cites this paper
• A spline-based tool to assess and visualize the calibration of multiclass risk predictions

  2015cites this paper
• What subject matter questions motivate the use of machine learning approaches compared to statistical models for probability prediction?

  2014influential citation
• Class probability estimation for medical studies

  2014influential citation
• Risk prediction with machine learning and regression methods

  2014influential citation
• Variable selection in large margin classifier‐based probability estimation with high‐dimensional predictors

  2014cites this paper
• Probability estimation with machine learning methods for dichotomous and multicategory outcome: Theory

  2014influential citation
• Machine learning versus statistical modeling

  2014influential citation
• Rejoinder

  2014cites this paper
• Probability estimation and machine learning—Editorial

  2014cites this paper