Machine learning models for the identification of prognostic and predictive cancer biomarkers: a systematic review
The identification of biomarkers plays a crucial role in personalized medicine, both in the
clinical and research settings. However, the contrast between predictive and prognostic …
clinical and research settings. However, the contrast between predictive and prognostic …
Subgroup identification for precision medicine: A comparative review of 13 methods
Natural heterogeneity in patient populations can make it very hard to develop treatments that
benefit all patients. As a result, an important goal of precision medicine is identification of …
benefit all patients. As a result, an important goal of precision medicine is identification of …
Tutorial in biostatistics: data‐driven subgroup identification and analysis in clinical trials
I Lipkovich, A Dmitrienko… - Statistics in …, 2017 - Wiley Online Library
It is well known that both the direction and magnitude of the treatment effect in clinical trials
are often affected by baseline patient characteristics (generally referred to as biomarkers) …
are often affected by baseline patient characteristics (generally referred to as biomarkers) …
The predictive approaches to treatment effect heterogeneity (PATH) statement: explanation and elaboration
DM Kent, D Van Klaveren, JK Paulus… - Annals of internal …, 2020 - acpjournals.org
The PATH (Predictive Approaches to Treatment effect Heterogeneity) Statement was
developed to promote the conduct of, and provide guidance for, predictive analyses of …
developed to promote the conduct of, and provide guidance for, predictive analyses of …
[图书][B] Adaptive treatment strategies in practice: planning trials and analyzing data for personalized medicine
MR Kosorok, EEM Moodie - 2015 - SIAM
The study of new medical treatments, and sequences of treatments, is inextricably linked
with statistics. Without statistical estimation and inference, we are left with case studies and …
with statistics. Without statistical estimation and inference, we are left with case studies and …
A general statistical framework for subgroup identification and comparative treatment scoring
Many statistical methods have recently been developed for identifying subgroups of patients
who may benefit from different available treatments. Compared with the traditional outcome …
who may benefit from different available treatments. Compared with the traditional outcome …
[图书][B] Dynamic treatment regimes: Statistical methods for precision medicine
Dynamic Treatment Regimes: Statistical Methods for Precision Medicine provides a
comprehensive introduction to statistical methodology for the evaluation and discovery of …
comprehensive introduction to statistical methodology for the evaluation and discovery of …
The oncology biomarker discovery framework reveals cetuximab and bevacizumab response patterns in metastatic colorectal cancer
AJ Ohnmacht, A Stahler, S Stintzing, DP Modest… - Nature …, 2023 - nature.com
Precision medicine has revolutionised cancer treatments; however, actionable biomarkers
remain scarce. To address this, we develop the Oncology Biomarker Discovery (OncoBird) …
remain scarce. To address this, we develop the Oncology Biomarker Discovery (OncoBird) …
Heterogeneous employment effects of job search programs: A machine learning approach
We systematically investigate the effect heterogeneity of job search programs for
unemployed workers. To investigate possibly heterogeneous employment effects, we …
unemployed workers. To investigate possibly heterogeneous employment effects, we …
Decision making and uncertainty quantification for individualized treatments using Bayesian Additive Regression Trees
BR Logan, R Sparapani… - Statistical methods in …, 2019 - journals.sagepub.com
Individualized treatment rules can improve health outcomes by recognizing that patients
may respond differently to treatment and assigning therapy with the most desirable predicted …
may respond differently to treatment and assigning therapy with the most desirable predicted …