Heidi Seibold

University of Zurich | UZH · Epidemiology, Biostatistics and Prevention Institute

Study objective Early post-operative delirium is a common perioperative complication in the post anesthesia care unit. To date it is unknown if a specific anesthetic regime can affect the incidence of delirium after surgery. Our objective was to examine the effect of volatile anesthetics on post-operative delirium. Design Single Center Observation...

Estimation of heterogeneous treatment effects (HTE) is of prime importance in many disciplines, ranging from personalized medicine to economics among many others. Random forests have been shown to be a flexible and powerful approach to HTE estimation in both randomized trials and observational studies. In particular "causal forests", introduced by...

OpenML is an online machine learning platform where researchers can easily share data, machine learning tasks and experiments as well as organize them online to work and collaborate more efficiently. In this paper, we present an R package to interface with the OpenML platform and illustrate its usage in combination with the machine learning R packa...

We investigate the effect of the proportional hazards assumption on prognostic and predictive models of the survival time of patients suffering from amyotrophic lateral sclerosis. We theoretically compare the underlying model formulations of several variants of survival forests and implementations thereof, including random forests for survival, con...

Typical models estimating treatment effects assume that the treatment effect is the same for all individuals. Model-based recursive partitioning allows to relax this assumption and to estimate stratified treatment effects (model-based trees) or even personalised treatment effects (model-based forests). With model-based trees one can compute treatme...

We investigate the effect of the proportional hazards assumption on prognostic and predictive models of the survival time of patients suffering from amyotrophic lateral sclerosis (ALS). We theoretically compare the underlying model formulations of several variants of survival forests and implementations thereof, including random forests for surviva...

The 'Treatment for Adolescents with Depression Study' (TADS, ClinicalTrials.gov, identifier: NCT00006286) was a cornerstone, randomized controlled trial evaluating the effectiveness of standard treatment options for major depression in adolescents. Whereas previous TADS analyses examined primarily effect modifications of treatment-placebo differenc...

The ‘Treatment for Adolescents with Depression Study’ (TADS, ClinicalTrials.gov, identifier: NCT00006286) was a cornerstone, randomized controlled trial evaluating the effectiveness of standard treatment options for major depression in adolescents. Whereas previous TADS analyses examined effect modifications of treatment-placebo differences by vari...

In biomedical research, boosting-based regression approaches have gained much attention in the last decade. Their intrinsic variable selection procedure and ability to shrink the estimates of the regression coefficients toward 0 make these techniques appropriate to fit prediction models in the case of high-dimensional data, e.g. gene expressions. T...

Randomized controlled trials (RCTs) usually enroll heterogeneous study population, and thus it is interesting to identify subgroups of patients for whom the treatment may be beneficial or harmful. A variety of methods have been developed to do such kind of post hoc analyses. Conventional generalized linear model is able to include prognostic variab...

An important task in early-phase drug development is to identify patients, which respond better or worse to an experimental treatment. While a variety of different subgroup identification methods have been developed for the situation of randomized clinical trials that study an experimental treatment and control, much less work has been done in the...

A treatment for a complicated disease might be helpful for some but not all patients, which makes predicting the treatment effect for new patients important yet challenging. Here we develop a method for predicting the treatment effect based on patient characteristics and use it for predicting the effect of the only drug (Riluzole) approved for trea...

Model-based trees are used to find subgroups in data which differ with respect to model parameters. In some applications it is natural to keep some parameters fixed globally for all observations while asking if and how other parameters vary across the subgroups. Existing implementations of model-based trees can only deal with the scenario where all...

OpenML is an online machine learning platform where researchers can automatically log and share data, code, and experiments, and organize them online to work and collaborate more effectively. We present an R package to interface the OpenML platform and illustrate its usage both as a stand-alone package and in combination with the mlr machine learni...

The identification of patient subgroups with differential treatment effects is the first step towards individualised treatments. A current draft guideline by the EMA discusses potentials and problems in subgroup analyses and formulated challenges to the development of appropriate statistical procedures for the data-driven identification of patient...

A treatment for a complicated disease may be helpful for some but not all patients, which makes predicting the treatment effect for new patients important yet challenging. Here we develop a method for predicting the treatment effect based on patient char- acteristics and use it for predicting the effect of the only drug (Riluzole) approved for trea...

In biomedical research, boosting-based regression approaches have gained much attention in the last decade. Their intrinsic variable selection procedure and their ability to shrink the estimates of the regression coefficients toward 0 make these techniques appropriate to fit prediction models in the case of high-dimensional data, e.g. gene expressi...

In Central Europe, protected areas are too small to ensure survival of populations of large carnivores. In the surrounding areas, these species are often persecuted due to competition with game hunters. Therefore, understanding how predation intensity varies spatio-temporally across areas with different levels of protection is fundamental. We inves...

Invertebrates outcompete vertebrate facultative scavengers in simulated lynx kills in the Bavarian Forest National Park, Germany.— Understanding the role of scavengers in ecosystems is important for species conservation and wildlife management. We used road–killed animals, 15 in summer 2003 (June–August) and nine in winter 2003/2004 (from November...