论文检索

肿瘤生长的空间统计分析AI 解读

Growth models for tumors commonly are developed for a one-dimensional summary (e.g., number of cells, volume). At the supracellular level, however, ignoring tumor shape leads to oversimplification of the growth mechanism. For example, an oncologist would view the discovery of a compact tumor of volume v differently from the discovery of two osculatory compact tumors each of volume v/2. This article presents a growth model that uses shape information at a previous time to…

肿瘤生长的空间统计分析AI 解读

Growth models for tumors commonly are developed for a one-dimensional summary (e.g., number of cells, volume). At the supracellular level, however, ignoring tumor shape leads to oversimplification of the growth mechanism. For example, an oncologist would view the discovery of a compact tumor of volume v differently from the discovery of two osculatory compact tumors each of volume v/2. This article presents a growth model that uses shape information at a previous time to…

比较实验与小区域估计中的贝叶斯及非贝叶斯程序：计算、频率学性质与联系AI 解读

The estimation of a treatment contrast from experimental data and the estimation of a small-area mean are special cases of the prediction of the realization of a linear combination of fixed and random effects in a possibly unbalanced two-part mixed linear model. In this article a Bayesian approach to point and interval prediction is presented and its computational requirements are examined. Differences between the Bayesian approach and the traditional (classical) approach…