Using the SAEM algorithm for mechanistic joint models characterizing the relationship between nonlinear PSA kinetics and survival in prostate cancer patients.
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Nonlinear joint models for individual dynamic prediction of risk of death using Hamiltonian Monte Carlo: application to metastatic prostate cancer.Mathematical modeling of efficacy and safety for anticancer drugs clinical development.Development and performance of npde for the evaluation of time-to-event models.Ebola viral dynamics in nonhuman primates provides insights into virus immuno-pathogenesis and antiviral strategies
P2860
Using the SAEM algorithm for mechanistic joint models characterizing the relationship between nonlinear PSA kinetics and survival in prostate cancer patients.
description
2016 nî lūn-bûn
@nan
2016年の論文
@ja
2016年論文
@yue
2016年論文
@zh-hant
2016年論文
@zh-hk
2016年論文
@zh-mo
2016年論文
@zh-tw
2016年论文
@wuu
2016年论文
@zh
2016年论文
@zh-cn
name
Using the SAEM algorithm for m ...... l in prostate cancer patients.
@en
Using the SAEM algorithm for m ...... l in prostate cancer patients.
@nl
type
label
Using the SAEM algorithm for m ...... l in prostate cancer patients.
@en
Using the SAEM algorithm for m ...... l in prostate cancer patients.
@nl
prefLabel
Using the SAEM algorithm for m ...... l in prostate cancer patients.
@en
Using the SAEM algorithm for m ...... l in prostate cancer patients.
@nl
P2093
P2860
P356
P1433
P1476
Using the SAEM algorithm for m ...... l in prostate cancer patients.
@en
P2093
Bernard Sébastien
Christine Veyrat-Follet
France Mentré
Jérémie Guedj
Solène Desmée
P2860
P304
P356
10.1111/BIOM.12537
P407
P577
2016-05-05T00:00:00Z