Clinical risk prediction with random forests for survival, longitudinal, and multivariate (RF-SLAM) data analysis
Published 2019 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Clinical risk prediction with random forests for survival, longitudinal, and multivariate (RF-SLAM) data analysis
Authors
Keywords
-
Journal
BMC Medical Research Methodology
Volume 20, Issue 1, Pages -
Publisher
Springer Science and Business Media LLC
Online
2019-12-31
DOI
10.1186/s12874-019-0863-0
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Poor performance of clinical prediction models: the harm of commonly applied methods
- (2018) Ewout W. Steyerberg et al. JOURNAL OF CLINICAL EPIDEMIOLOGY
- Estimating Individual Treatment Effect in Observational Data Using Random Forest Methods
- (2018) Min Lu et al. JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS
- Estimation and Inference of Heterogeneous Treatment Effects using Random Forests
- (2018) Stefan Wager et al. JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
- Sudden Death Risk-Stratification in 2018–2019: The Old and the New
- (2018) Sarah Zaman et al. Heart Lung and Circulation
- An Overview of Joint Modeling of Time-to-Event and Longitudinal Outcomes
- (2018) Grigorios Papageorgiou et al. Annual Review of Statistics and Its Application
- Current Device Therapies for Sudden Cardiac Death Prevention – the ICD, Subcutaneous ICD and Wearable ICD
- (2018) David Chieng et al. Heart Lung and Circulation
- The Contemporary Era of Sudden Cardiac Death and Ventricular Arrhythmias: Basic Concepts, Recent Developments and Future Directions
- (2018) Haris M. Haqqani et al. Heart Lung and Circulation
- A Tutorial on Evaluating the Time-Varying Discrimination Accuracy of Survival Models Used in Dynamic Decision Making
- (2018) Aasthaa Bansal et al. MEDICAL DECISION MAKING
- Impaired left atrial function predicts inappropriate shocks in primary prevention implantable cardioverter-defibrillator candidates
- (2017) Susumu Tao et al. JOURNAL OF CARDIOVASCULAR ELECTROPHYSIOLOGY
- Sudden Cardiac Arrest Risk Assessment
- (2017) Robert J. Myerburg et al. JAMA Cardiology
- Development and Validation of a Sudden Cardiac Death Prediction Model for the General PopulationClinical Perspective
- (2016) Rajat Deo et al. CIRCULATION
- Associations between scar characteristics by cardiac magnetic resonance and changes in left ventricular ejection fraction in primary prevention defibrillator recipients
- (2016) Yiyi Zhang et al. HEART RHYTHM
- $$L_1$$ L 1 splitting rules in survival forests
- (2016) Hoora Moradian et al. LIFETIME DATA ANALYSIS
- Nonparametric survival analysis using Bayesian Additive Regression Trees (BART)
- (2016) Rodney A. Sparapani et al. STATISTICS IN MEDICINE
- Calibrating random forests for probability estimation
- (2016) Theresa Dankowski et al. STATISTICS IN MEDICINE
- Machine Learning in Medicine
- (2015) R. C. Deo CIRCULATION
- The Spectrum of Epidemiology Underlying Sudden Cardiac Death
- (2015) M. Hayashi et al. CIRCULATION RESEARCH
- Clinical and serum-based markers are associated with death within 1 year of de novo implant in primary prevention ICD recipients
- (2015) Yiyi Zhang et al. HEART RHYTHM
- Contemporary rates of appropriate shock therapy in patients who receive implantable device therapy in a real-world setting: From the Israeli ICD Registry
- (2015) Avi Sabbag et al. HEART RHYTHM
- Protein Biomarkers Identify Patients Unlikely to Benefit From Primary Prevention Implantable Cardioverter Defibrillators
- (2014) Alan Cheng et al. Circulation-Arrhythmia and Electrophysiology
- Risk stratification for sudden cardiac death: current status and challenges for the future
- (2014) H. J. J. Wellens et al. EUROPEAN HEART JOURNAL
- Towards better clinical prediction models: seven steps for development and an ABCD for validation
- (2014) E. W. Steyerberg et al. EUROPEAN HEART JOURNAL
- Characteristics and Outcomes of Patients Receiving New and Replacement Implantable Cardioverter-Defibrillators
- (2013) Daniel B. Kramer et al.
- Consumer credit risk: Individual probability estimates using machine learning
- (2013) Jochen Kruppa et al. EXPERT SYSTEMS WITH APPLICATIONS
- Prospective Observational Study of Implantable Cardioverter‐Defibrillators in Primary Prevention of Sudden Cardiac Death: Study Design and Cohort Description
- (2013) Alan Cheng et al. Journal of the American Heart Association
- Combined Cardiac Magnetic Resonance Imaging and C-Reactive Protein Levels Identify a Cohort at Low Risk for Defibrillator Firings and Death
- (2012) Katherine C. Wu et al. Circulation-Cardiovascular Imaging
- Risk estimation and risk prediction using machine-learning methods
- (2012) Jochen Kruppa et al. HUMAN GENETICS
- Overview of random forest methodology and practical guidance with emphasis on computational biology and bioinformatics
- (2012) Anne-Laure Boulesteix et al. Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery
- Screening for Sudden Cardiac Death in the Young
- (2011) Jonathan R. Kaltman et al. CIRCULATION
- Probability Machines
- (2011) J. D. Malley et al. METHODS OF INFORMATION IN MEDICINE
- Subgroup identification from randomized clinical trial data
- (2011) Jared C. Foster et al. STATISTICS IN MEDICINE
- Sudden Cardiac Death Prediction and Prevention
- (2010) Glenn I. Fishman et al. CIRCULATION
- Use of Brier score to assess binary predictions
- (2010) Kaspar Rufibach JOURNAL OF CLINICAL EPIDEMIOLOGY
- Bayesian Nonparametric Modeling for Causal Inference
- (2010) Jennifer L. Hill JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS
- Improved Logrank-Type Tests for Survival Data Using Adaptive Weights
- (2009) Song Yang et al. BIOMETRICS
- Random survival forests
- (2008) Hemant Ishwaran et al. Annals of Applied Statistics
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreDiscover Peeref hubs
Discuss science. Find collaborators. Network.
Join a conversation