Individual dynamic prediction of clinical endpoint from large dimensional longitudinal biomarker history: a landmark approach

Super Learner for Survival Data Prediction

(2020) Marzieh K. Golmakani et al.   International Journal of Biostatistics

Incorporating longitudinal biomarkers for dynamic risk prediction in the era of big data: A pseudo‐observation approach

(2020) Lili Zhao et al.   STATISTICS IN MEDICINE

A review of spline function procedures in R

(2019) Aris Perperoglou et al.   BMC Medical Research Methodology

Landmark Models for Optimizing the Use of Repeated Measurements of Risk Factors in Electronic Health Records to Predict Future Disease Risk

(2018) Ellie Paige et al.   AMERICAN JOURNAL OF EPIDEMIOLOGY

DeepSurv: personalized treatment recommender system using a Cox proportional hazards deep neural network

(2018) Jared L. Katzman et al.   BMC Medical Research Methodology

Individual dynamic predictions using landmarking and joint modelling: Validation of estimators and robustness assessment

(2018) Loïc Ferrer et al.   STATISTICAL METHODS IN MEDICAL RESEARCH

Estimation of Extended Mixed Models Using Latent Classes and Latent Processes: The R Package lcmm

(2017) Cécile Proust-Lima et al.   Journal of Statistical Software

On longitudinal prediction with time-to-event outcome: Comparison of modeling options

(2016) Marlena Maziarz et al.   BIOMETRICS

Moving beyond regression techniques in cardiovascular risk prediction: applying machine learning to address analytic challenges

(2016) Benjamin A. Goldstein et al.   EUROPEAN HEART JOURNAL

The use of repeated blood pressure measures for cardiovascular risk prediction: a comparison of statistical models in the ARIC study

(2016) Michael J. Sweeting et al.   STATISTICS IN MEDICINE

Regularization Paths for Cox's Proportional Hazards Model via Coordinate Descent

(2015) Noah Simon et al.   Journal of Statistical Software

Evaluating Random Forests for Survival Analysis Using Prediction Error Curves

(2015) Ulla B. Mogensen et al.   Journal of Statistical Software

Deviance residuals-based sparse PLS and sparse kernel PLS regression for censored data

(2014) Philippe Bastien et al.   BIOINFORMATICS

Quantifying and comparing dynamic predictive accuracy of joint models for longitudinal marker and time-to-event in presence of censoring and competing risks

(2014) Paul Blanche et al.   BIOMETRICS

Random survival forests for competing risks

(2014) H. Ishwaran et al.   BIOSTATISTICS

Random Forest ensembles for detection and prediction of Alzheimer's disease with a good between-cohort robustness

(2014) A.V. Lebedev et al.   NeuroImage-Clinical

Real-Time Individual Predictions of Prostate Cancer Recurrence Using Joint Models

(2013) Jeremy M. G. Taylor et al.   BIOMETRICS

Estimating and comparing time-dependent areas under receiver operating characteristic curves for censored event times with competing risks

(2013) Paul Blanche et al.   STATISTICS IN MEDICINE

Dynamic Predictions and Prospective Accuracy in Joint Models for Longitudinal and Time-to-Event Data

(2011) Dimitris Rizopoulos   BIOMETRICS

On Estimating the Relationship between Longitudinal Measurements and Time-to-Event Data Using a Simple Two-Stage Procedure

(2010) Paul S. Albert et al.   BIOMETRICS

Sparse partial least squares regression for simultaneous dimension reduction and variable selection

(2010) Hyonho Chun et al.   JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY

L1Penalized Estimation in the Cox Proportional Hazards Model

(2009) Jelle J. Goeman   BIOMETRICAL JOURNAL

Development and validation of a dynamic prognostic tool for prostate cancer recurrence using repeated measures of posttreatment PSA: a joint modeling approach

(2009) C. Proust-Lima et al.   BIOSTATISTICS

Random survival forests

(2008) Hemant Ishwaran et al.   Annals of Applied Statistics

Semiparametric Modeling of Longitudinal Measurements and Time-to-Event Data-A Two-Stage Regression Calibration Approach

(2008) Wen Ye et al.   BIOMETRICS