Results 21 to 30 of about 17,500,545 (334)
Neutrosophic Generalized Rayleigh Distribution with Application [PDF]
In this paper, we consider the neutrosophic generalized Rayleigh distribution (NGRD). Various neutrosophic properties of NGRD are developed and discussed. The developed distribution is specifically more useful to model indeterminate data which are skewed
Mina Norouzirad +2 more
doaj +1 more source
To explore the population quantitative characteristics and regional distribution of wild Viburnum plants in Southwest Hubei, and reveal the survival status and development trend of the following five Viburnum species: V. erosum, V.
Huandun ZHAO +6 more
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Breast cancer is the most common cancer in women and the leading cause of cancer-related death in Indonesia. Analysis of survival data is important for improving the treatment and care of breast cancer patients. This study aims to estimate the parameters,
Ardi Kurniawan +2 more
doaj +1 more source
Learning Survival Distribution with Implicit Survival Function
Survival analysis aims at modeling the relationship between covariates and event occurrence with some untracked (censored) samples. In implementation, existing methods model the survival distribution with strong assumptions or in a discrete time space for likelihood estimation with censorship, which leads to weak generalization.
Ling, Yu, Tan, Weimin, Yan, Bo
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Survival as a Function of Life Expectancy [PDF]
It is well known that life expectancy can be expressed as an integral of the survival curve. The reverse - that the survival function can be expressed as an integral of life expectancy - is also true.
James Vaupel, Maxim Finkelstein
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Delayed graft function influences renal function but not survival [PDF]
In renal transplantation, the impact of delayed graft function (DGF) on prognosis is controversial. We analyzed the risk factors of DGF and its impact on graft function and prognosis.Seven hundred thirty-four cadaveric renal transplants performed between 1983 and 1997 were analyzed.
Boom, Henk +4 more
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Mortality as a Function of Survival
Abstract Everyone has a chronological age. Because survivorship declines relentlessly in populations with age-specific death rates greater than zero, everyone also has a survivorship age (“s-age”), the age at which a proportion s of the population is still alive. S-ages can be estimated for both periods and cohorts. While trajectories of
Jesús-Adrián Alvarez, James W. Vaupel
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Schur-concave survival functions and survival analysis
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Richard E. Barlow, SPIZZICHINO, Fabio
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Preimplantation biopsy predicts delayed graft function, glomerular filtration rate and long-term graft survival of transplanted kidneys [PDF]
Background The predictive value of preimplantation biopsies for long-term graft function is often limited by conflicting results. The aim of this study was to evaluate the influence of time-zero graft biopsy histological scores on early and late graft ...
Bianchi, Valentina +10 more
core +2 more sources
Analysis of survival data with cross-effects of survival functions [PDF]
We present a model and semiparametric estimation procedures for analysis of survival data with cross-effects (CE) of survival functions. Finite sample properties of the estimators are analyzed by simulation. A goodness-of-fit test for the proportional hazards model against the CE model is proposed. The well known data concerning effects of chemotherapy
Bagdonavicius, Vilijandas +2 more
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