Statistical methods in medical research
Jan 23, 2025
One primary goal of precision medicine is to estimate the individualized treatment rules that optimize patients' health outcomes based on individual characteristics. Health studies with multiple treatments are commonly seen in practice. However, most...
Statistical methods in medical research
Mar 19, 2024
Observational data (e.g. electronic health records) has become increasingly important in evidence-based research on dynamic treatment regimes, which tailor treatments over time to patients based on their characteristics and evolving clinical history....
Statistical methods in medical research
Nov 8, 2023
The mixture cure rate model is the most commonly used cure rate model in the literature. In the context of mixture cure rate model, the standard approach to model the effect of covariates on the cured or uncured probability is to use a logistic funct...
Statistical methods in medical research
Apr 3, 2023
The uncertainty in predictions from deep neural network analysis of medical imaging is challenging to assess but potentially important to include in subsequent decision-making. Using data from diabetic retinopathy detection, we present an empirical e...
Statistical methods in medical research
Oct 25, 2021
Variable selection in the presence of both missing covariates and outcomes is an important statistical research topic. Parametric regression are susceptible to misspecification, and as a result are sub-optimal for variable selection. Flexible machine...
Statistical methods in medical research
Sep 1, 2021
Machine learning algorithms are increasingly used in the clinical literature, claiming advantages over logistic regression. However, they are generally designed to maximize the area under the receiver operating characteristic curve. While area under ...
Statistical methods in medical research
Jun 1, 2021
There is a well-established tradition within the statistics literature that explores different techniques for reducing the dimensionality of large feature spaces. The problem is central to machine learning and it has been largely explored under the u...
Statistical methods in medical research
Apr 13, 2021
Machine learning approaches are increasingly suggested as tools to improve prediction of clinical outcomes. We aimed to identify when machine learning methods perform better than a classical learning method. We hereto examined the impact of the data-...
Statistical methods in medical research
Sep 12, 2019
Model selection and performance assessment for prediction models are important tasks in machine learning, e.g. for the development of medical diagnosis or prognosis rules based on complex data. A common approach is to select the best model via cross-...
Statistical methods in medical research
May 2, 2018
Data-adaptive methods have been proposed to estimate nuisance parameters when using doubly robust semiparametric methods for estimating marginal causal effects. However, in the presence of near practical positivity violations, these methods can produ...