Results 31 to 40 of about 426,709 (217)
DeepSurv: personalized treatment recommender system using a Cox proportional hazards deep neural network [PDF]
BMC Medical Research Methodology, 2016 BackgroundMedical practitioners use survival models to explore and understand the relationships between patients’ covariates (e.g. clinical and genetic features) and the effectiveness of various treatment options. Standard survival models like the linear
Jared Katzman +5 more
semanticscholar +1 more source
A Federated Cox Model with Non-proportional Hazards
, 2022 Recent research has shown the potential for neural networks to improve upon classical survival models such as the Cox model, which is widely used in clinical practice. Neural networks, however, typically rely on data that are centrally available, whereas healthcare data are frequently held in secure silos.
D. Kai Zhang +2 more
openaire +3 more sources
Relaxing the independent censoring assumption in the Cox proportional hazards model using multiple imputation. [PDF]
Stat Med, 2014 The Cox proportional hazards model is frequently used in medical statistics. The standard methods for fitting this model rely on the assumption of independent censoring.
Jackson D +5 more
europepmc +2 more sources
Comparison of radiomic feature aggregation methods for patients with multiple tumors
Scientific Reports, 2021 Radiomic feature analysis has been shown to be effective at analyzing diagnostic images to model cancer outcomes. It has not yet been established how to best combine radiomic features in cancer patients with multifocal tumors.
Enoch Chang +7 more
doaj +1 more source
Cox regression survival analysis with compositional covariates: application to modelling mortality risk from 24-h physical activity patterns [PDF]
, 2020 Survival analysis is commonly conducted in medical and public health research to assess the association of an exposure or intervention with a hard end outcome such as mortality. The Cox (proportional hazards) regression model is probably the most popular
Chastin, S.F.M. +4 more
core +1 more source
Bayesian random threshold estimation in a Cox proportional hazards cure model [PDF]
, 2013 Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/102705/1/sim5964 ...
Bellile, Emily L. +3 more
core +1 more source
BMC Research Notes, 2017 Background Uganda just like any other Sub-Saharan African country, has a high under-five child mortality rate. To inform policy on intervention strategies, sound statistical methods are required to critically identify factors strongly associated with ...
Justine B. Nasejje, Henry Mwambi
doaj +1 more source
A penalized Cox proportional hazards model with multiple time-varying exposures [PDF]
, 2017 In recent pharmacoepidemiology research, the increasing use of electronic medication dispensing data provides an unprecedented opportunity to examine various health outcomes associated with long-term medication usage.
Gao, Sujuan, Liu, Hai, Wang, Chenkun
core +1 more source
Testing proportional hazards for specified covariates
Modern Stochastics: Theory and Applications, 2019 Tests for proportional hazards assumption concerning specified covariates or groups of covariates are proposed. The class of alternatives is wide: log-hazard rates under different values of covariates may cross, approach, go away.
Vilijandas Bagdonavičius +1 more
doaj +1 more source
BMC Bioinformatics, 2021 Background The Cox proportional hazards model is commonly used to predict hazard ratio, which is the risk or probability of occurrence of an event of interest.
Eu-Tteum Baek +6 more
doaj +1 more source