Results 11 to 20 of about 4,464,251 (309)
Stroke outcome in clinical trial patients deriving from different countries [PDF]
<p><b>Background and Purpose:</b> Stroke incidence and outcome vary widely within and across geographical locations. We examined whether differences in index stroke severity, stroke risk factors, mortality, and stroke outcome across ...
Lees, K.R. +8 more
core +7 more sources
Benchmarking survival outcomes: A funnel plot for survival data [PDF]
Benchmarking is commonly used in many healthcare settings to monitor clinical performance, with the aim of increasing cost-effectiveness and safe care of patients. The funnel plot is a popular tool in visualizing the performance of a healthcare center in relation to other centers and to a target, taking into account statistical uncertainty.
Putter, H. +7 more
openaire +6 more sources
Deep learning for survival outcomes [PDF]
Deep learning is a class of machine learning algorithms that are popular for building risk prediction models. When observations are censored, the outcomes are only partially observed and standard deep learning algorithms cannot be directly applied. We develop a new class of deep learning algorithms for outcomes that are potentially censored. To account
Jon Arni Steingrimsson +1 more
openaire +3 more sources
Survival Outcomes and Prognostic Factors in Glioblastoma
Background: IDH-wildtype glioblastoma is the most common malignant primary brain tumour in adults. As there is limited information on prognostic factors outside of clinical trials; thus, we conducted a retrospective study to characterise the glioblastoma population at our centre.
Nicholas F. Brown +7 more
openaire +3 more sources
Survival Outcomes in Elderly Patients With Glioblastoma [PDF]
Many elderly glioblastoma patients are excluded from randomised trials due to age, comorbidity or poor functional status. The purpose of this study was to describe the survival outcomes in all elderly patients with glioblastoma managed at a tertiary cancer centre.A retrospective chart review identified 235 elderly patients (age 65 years or over) with a
D S, Tsang +9 more
openaire +2 more sources
Bayesian Survival Modelling of University Outcomes [PDF]
SummaryDropouts and delayed graduations are critical issues in higher education systems world wide. A key task in this context is to identify risk factors associated with these events, providing potential targets for mitigating policies. For this, we employ a discrete time competing risks survival model, dealing simultaneously with university outcomes ...
Vallejos, Catalina, Steel, Mark F. J.
openaire +3 more sources
A pebble rolling down a hill can easily be studied. Even from the perspective of one who stands before the pebble, the forces that set it in motion and the path that it takes can be considered, the anomalous bounces contemplated. The absence of danger provides the observer with time for reflection.
openaire +2 more sources
Cancer survival among children of Turkish descent in Germany 1980–2005: a registry-based analysis [PDF]
Spix C, Spallek J, Kaatsch P, Razum O, Zeeb H. Cancer survival among children of Turkish descent in Germany 1980–2005: a registry-based analysis. BMC Cancer.
Spix Claudia +14 more
core +2 more sources
Pitfalls of the concordance index for survival outcomes
Prognostic models are useful tools for assessing a patient's risk of experiencing adverse health events. In practice, these models must be validated before implementation to ensure that they are clinically useful. The concordance index (C‐Index) is a popular statistic that is used for model validation, and it is often applied to models with binary or ...
Nicholas Hartman +3 more
openaire +3 more sources
The formula for survival in resuscitation
The International Liaison Committee on Resuscitation (ILCOR) Advisory Statement on Education and Resuscitation in 2003 included a hypothetical formula - 'the formula for survival' (FfS) - whereby three interactive factors, guideline quality (science ...
Nadkarni, Vinay M. +15 more
core +2 more sources

