Cargando…
Construction of an individualized brain metabolic network in patients with advanced non-small cell lung cancer by the Kullback-Leibler divergence-based similarity method: A study based on 18F-fluorodeoxyglucose positron emission tomography
BACKGROUND: Lung cancer has one of the highest mortality rates of all cancers, and non-small cell lung cancer (NSCLC) accounts for the vast majority (about 85%) of lung cancers. Psychological and cognitive abnormalities are common in cancer patients, and cancer information can affect brain function...
Autores principales: | Yu, Jie, Hua, Lin, Cao, Xiaoling, Chen, Qingling, Zeng, Xinglin, Yuan, Zhen, Wang, Ying |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10036828/ https://www.ncbi.nlm.nih.gov/pubmed/36969017 http://dx.doi.org/10.3389/fonc.2023.1098748 |
Ejemplares similares
-
Kullback–Leibler divergence and the Pareto–Exponential approximation
por: Weinberg, G. V.
Publicado: (2016) -
Computation of Kullback–Leibler Divergence in Bayesian Networks
por: Moral, Serafín, et al.
Publicado: (2021) -
Kullback Leibler divergence in complete bacterial and phage genomes
por: Akhter, Sajia, et al.
Publicado: (2017) -
Kullback–Leibler Divergence of a Freely Cooling Granular Gas
por: Megías, Alberto, et al.
Publicado: (2020) -
A data assimilation framework that uses the Kullback-Leibler divergence
por: Pimentel, Sam, et al.
Publicado: (2021)