Zobrazeno 1 - 10
of 40
pro vyhledávání: '"Anthony CC"'
Autor:
Paul R Barber, Rami Mustapha, Fabian Flores-Borja, Giovanna Alfano, Kenrick Ng, Gregory Weitsman, Luigi Dolcetti, Ali Abdulnabi Suwaidan, Felix Wong, Jose M Vicencio, Myria Galazi, James W Opzoomer, James N Arnold, Selvam Thavaraj, Shahram Kordasti, Jana Doyle, Jon Greenberg, Magnus T Dillon, Kevin J Harrington, Martin Forster, Anthony CC Coolen, Tony Ng
Publikováno v:
eLife, Vol 11 (2022)
Background: Advanced head and neck squamous cell carcinoma (HNSCC) is associated with a poor prognosis, and biomarkers that predict response to treatment are highly desirable. The primary aim was to predict progression-free survival (PFS) with a mult
Externí odkaz:
https://doaj.org/article/f01407f956a24b9e8f9a0385ed5d4e28
In cancer research, overall survival and progression free survival are often analyzed with the Cox model. To estimate accurately the parameters in the model, sufficient data and, more importantly, sufficient events need to be observed. In practice, t
Externí odkaz:
http://arxiv.org/abs/2404.17464
To estimate accurately the parameters of a regression model, the sample size must be large enough relative to the number of possible predictors for the model. In practice, sufficient data is often lacking, which can lead to overfitting of the model a
Externí odkaz:
http://arxiv.org/abs/2402.02898
Identifying predictive factors for an outcome of interest via a multivariable analysis is often difficult when the data set is small. Combining data from different medical centers into a single (larger) database would alleviate this problem, but is i
Externí odkaz:
http://arxiv.org/abs/2302.07677
Autor:
Mozeika, Alexander, Sheikh, Mansoor, Aguirre-Lopez, Fabian, Antenucci, Fabrizio, Coolen, Anthony CC
Publikováno v:
Phys. Rev. E 103, 042142 (2021)
It is clear that conventional statistical inference protocols need to be revised to deal correctly with the high-dimensional data that are now common. Most recent studies aimed at achieving this revision rely on powerful approximation techniques, tha
Externí odkaz:
http://arxiv.org/abs/2009.13229
We analyze maximum entropy random graph ensembles with constrained degrees, drawn from arbitrary degree distributions, and a tuneable number of 3-loops (triangles). We find that such ensembles generally exhibit two transitions, a clustering and a sha
Externí odkaz:
http://arxiv.org/abs/2008.11002
We present an analytical approach for describing spectrally constrained maximum entropy ensembles of finitely connected regular loopy graphs, valid in the regime of weak loop-loop interactions. We derive an expression for the leading two orders of th
Externí odkaz:
http://arxiv.org/abs/1907.06703
Autor:
Mozeika, Alexander, Coolen, Anthony CC
We use statistical mechanics to study model-based Bayesian data clustering. In this approach, each partition of the data into clusters is regarded as a microscopic system state, the negative data log-likelihood gives the energy of each state, and the
Externí odkaz:
http://arxiv.org/abs/1810.02627
Autor:
Mozeika, Alexander, Coolen, Anthony CC
Publikováno v:
Phys. Rev. E 98, 042133 (2018)
We show that model-based Bayesian clustering, the probabilistically most systematic approach to the partitioning of data, can be mapped into a statistical physics problem for a gas of particles, and as a result becomes amenable to a detailed quantita
Externí odkaz:
http://arxiv.org/abs/1709.01632
We introduce and analyse ensembles of 2-regular random graphs with a tuneable distribution of short cycles. The phenomenology of these graphs depends critically on the scaling of the ensembles' control parameters relative to the number of nodes. A ph
Externí odkaz:
http://arxiv.org/abs/1705.03743