Results 41 to 50 of about 1,623,179 (299)
Differentially Private Regression for Discrete-Time Survival Analysis [PDF]
In survival analysis, regression models are used to understand the effects of explanatory variables (e.g., age, sex, weight, etc.) to the survival probability. However, for sensitive survival data such as medical data, there are serious concerns about the privacy of individuals in the data set when medical data is used to fit the regression models. The
Thông T. Nguyên, Siu Cheung Hui
openaire +3 more sources
The paper presents a novel statistical approach for analyzing the daily coronavirus case and fatality statistics. The survival discretization method was used to generate a two-parameter discrete distribution.
Hassan M. Aljohani +6 more
doaj +1 more source
A scalable discrete-time survival model for neural networks
There is currently great interest in applying neural networks to prediction tasks in medicine. It is important for predictive models to be able to use survival data, where each patient has a known follow-up time and event/censoring indicator. This avoids information loss when training the model and enables generation of predicted survival curves.
Gensheimer, Michael F. +1 more
openaire +5 more sources
Background: The objective of this study was to construct a risk classification system integrating cell-free Epstein-Barr virus (cfEBV) DNA with T- and N- categories for better prognostication in nasopharyngeal carcinoma (NPC).
Fo-Ping Chen +14 more
doaj +1 more source
Which states matter? An application of an intelligent discretization method to solve a continuous POMDP in conservation biology. [PDF]
When managing populations of threatened species, conservation managers seek to make the best conservation decisions to avoid extinction. Making the best decision is difficult because the true population size and the effects of management are uncertain ...
Sam Nicol, Iadine Chadès
doaj +1 more source
ICTSurF: Implicit Continuous-Time Survival Functions with neural networks
Background and objective:: Recently, the rise of models based on deep neural networks (DNNs) has demonstrated enhanced effectiveness in survival analysis.
Chanon Puttanawarut +3 more
doaj +1 more source
The cosymmetric approach to the analysis of spatial structure of populations with amount of taxis [PDF]
We consider a mathematical model describing the competition for a heterogeneous resource of two populations on a one-dimensional area. Distribution of populations is governed by diffusion and directed migration, species growth obeys to the logistic law ...
Lyubov Evgenievna Alpeeva +1 more
doaj +1 more source
Lumped Approximation of a Transmission Line with an Alternative Geometric Discretization [PDF]
An electromagnetic one-dimensional transmission line represented in a distributed port-Hamiltonian form is lumped into a chain of subsystems which preserve the port-Hamiltonian structure with inputs and outputs in collocated form.
Scherpen, Jacquelien M.A., +3 more
core +1 more source
Double-stage discretization approaches for biomarker-based bladder cancer survival modeling
Bioinformatic techniques targeting gene expression data require specific analysis pipelines with the aim of studying properties, adaptation, and disease outcomes in a sample population.
Nascimben M., Venturin M., Rimondini L.
core +1 more source
Design and analysis strategies for robust microbiome ageing research
The gut microbiome changes with age and associates with age‐related morbidity and mortality, establishing it as a potential biomarker and intervention target for ageing. Realising this potential requires methodological rigour, yet distinguishing biological signals from methodological artefacts remains challenging across cohorts. This review provides an
Mark Olenik +5 more
wiley +1 more source

