Related references
Note: Only part of the references are listed.The Impact of Churn on Client Value in Health Insurance, Evaluation Using a Random Forest Under Various Censoring Mechanisms
Guillaume Gerber et al.
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION (2021)
A comparison of machine learning methods for survival analysis of high-dimensional clinical data for dementia prediction
Annette Spooner et al.
SCIENTIFIC REPORTS (2020)
A Comparison Study of Machine Learning (Random Survival Forest) and Classic Statistic (Cox Proportional Hazards) for Predicting Progression in High-Grade Glioma after Proton and Carbon Ion Radiotherapy
Xianxin Qiu et al.
FRONTIERS IN ONCOLOGY (2020)
Machine learning and atherosclerotic cardiovascular disease risk prediction in a multi-ethnic population
Andrew Ward et al.
NPJ DIGITAL MEDICINE (2020)
The c-index is not proper for the evaluation of -year predicted risks
Paul Blanche et al.
BIOSTATISTICS (2019)
A systematic review shows no performance benefit of machine learning over logistic regression for clinical prediction models
Evangelia Christodoulou et al.
JOURNAL OF CLINICAL EPIDEMIOLOGY (2019)
Big Data Toolsets to Pharmacometrics: Application of Machine Learning for Time-to-Event Analysis
Xiajing Gong et al.
CTS-CLINICAL AND TRANSLATIONAL SCIENCE (2018)
Ten-year prediction of suicide death using Cox regression and machine learning in a nationwide retrospective cohort study in South Korea
Soo Beom Choi et al.
JOURNAL OF AFFECTIVE DISORDERS (2018)
Machine learning models in electronic health records can outperform conventional survival models for predicting patient mortality in coronary artery disease
Andrew J. Steele et al.
PLOS ONE (2018)
Opportunities and challenges in developing risk prediction models with electronic health records data: a systematic review
Benjamin A. Goldstein et al.
JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION (2017)
Unbiased split variable selection for random survival forests using maximally selected rank statistics
Marvin N. Wright et al.
STATISTICS IN MEDICINE (2017)
A comparison of the conditional inference survival forest model to random survival forests based on a simulation study as well as on two applications with time-to-event data
Justine B. Nasejje et al.
BMC MEDICAL RESEARCH METHODOLOGY (2017)
Risk estimation and risk prediction using machine-learning methods
Jochen Kruppa et al.
HUMAN GENETICS (2012)
Support vector methods for survival analysis: a comparison between ranking and regression approaches
Vanya Van Belle et al.
ARTIFICIAL INTELLIGENCE IN MEDICINE (2011)
On the C-statistics for evaluating overall adequacy of risk prediction procedures with censored survival data
Hajime Uno et al.
STATISTICS IN MEDICINE (2011)
Individualised risk estimation and the nature of prevention
Christine Holmberg et al.
HEALTH RISK & SOCIETY (2010)
AUSDRISK: an Australian Type 2 Diabetes Risk Assessment Tool based on demographic, lifestyle and simple anthropometric measures
Lei Chen et al.
MEDICAL JOURNAL OF AUSTRALIA (2010)
The comparisons of random survival forests and Cox regression analysis with simulation and an application related to breast cancer
Imran Kurt Omurlu et al.
EXPERT SYSTEMS WITH APPLICATIONS (2009)
Prognosis and prognostic research: what, why, and how?
Karel G. M. Moons et al.
BMJ-BRITISH MEDICAL JOURNAL (2009)
RANDOM SURVIVAL FORESTS
Hemant Ishwaran et al.
ANNALS OF APPLIED STATISTICS (2008)
General cardiovascular risk profile for use in primary care - The Framingham Heart Study
Ralph B. D'Agostino et al.
CIRCULATION (2008)
Derivation and validation of QRISK, a new cardiovascular disease risk score for the United Kingdom: prospective open cohort study
Julia Hippisley-Cox et al.
BMJ-BRITISH MEDICAL JOURNAL (2007)
An accurate risk score based on anthropometric, dietary, and lifestyle factors to predict the development of type 2 diabetes
Matthias B. Schulze et al.
DIABETES CARE (2007)
Evaluating prediction rules for t-year survivors with censored regression models
Hajime Uno et al.
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION (2007)
Estimation of ten-year risk of fatal cardiovascular disease in Europe:: the SCORE project
RM Conroy et al.
EUROPEAN HEART JOURNAL (2003)
Cardiovascular disease risk factors in HIV patients -: association with antiretroviral therapy.: Results from the DAD study
N Friis-Moller et al.
AIDS (2003)