Results 241 to 250 of about 1,623,179 (299)

Discretization of nonlinear elliptic optimal control problems

, 1994
Chryssoverghi, I, Kokkinis, B
core  

First-passage-based boundary estimation in functional data. [PDF]

PLoS One
Kuzu AT, Celik N.
europepmc   +1 more source

Predictive value of 18F-FDG PET/CT delta radiomics model for prognosis after neoadjuvant therapy for locally advanced pancreatic cancer. [PDF]

Front Oncol
Chen QL, Yang LX, Li AM, Mao L, Qiu YD, Du J, He J.   +6 more
europepmc   +1 more source

Tabular transformer generative adversarial network for heterogeneous distribution in healthcare. [PDF]

Sci Rep
Kang HYJ, Ko M, Ryu KS.
europepmc   +1 more source

Neonatal Mortality in Burkina Faso: An Exploratory Analysis of Determinants and Geospatial Inequalities. [PDF]

Int J Public Health
Bassinga H.
europepmc   +1 more source

Predictor of Mortality in Obstructive Sleep Apnea: Results of Explainable Deep Learning-Based Survival Analysis from a 15-Year Follow-Up.

Respiration
Pagano G, Castellana G, D Apos Addio G, Palazzo L, Aliani M, Guido P, Berloco F, Marvulli PM, Suglia V, Colucci S, Lacedonia D, Bevilacqua V, Carone M.   +12 more
europepmc   +1 more source

Bayesian networks to estimate prognosis in vascular cognitive impairment and small vessel disease: integrated analyses of interdependent contributors to multiple outcomes

Overmars LM, Allaart C, Bron EE, Brunner La Rocca H, de Bresser J, Muller M, van Osch MJ, Teunissen C, Tijms BM, Wolters FJ, Biessels GJ.   +10 more
europepmc   +1 more source

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Discrete‐time survival data with longitudinal covariates

Statistics in Medicine, 2020
Survival analysis has been conventionally performed on a continuous time scale. In practice, the survival time is often recorded or handled on a discrete scale; when this is the case, the discrete‐time survival analysis would provide analysis results more relevant to the actual data scale.
Chi‐Chung Wen, Yi‐Hau Chen
openaire   +4 more sources

Discrete‐time survival trees

Canadian Journal of Statistics, 2009
AbstractTree‐based methods are frequently used in studies with censored survival time. Their structure and ease of interpretability make them useful to identify prognostic factors and to predict conditional survival probabilities given an individual's covariates.
Bou-Hamad, Imad, Larocque, Denis, Ben-Ameur, Hatem, Mâsse, Louise C., Vitaro, Frank, Tremblay, Richard E.   +5 more
openaire   +1 more source