Ideally, specific treatment for a cancer patient is decided by a multidisciplinary tumor board, integrating prior clinical experience, published data, and patient-specific factors to develop a ...

In a world of uncertainty and shifting narratives, this post proposes a new model for investing: Bayesian edge investing. Unlike modern portfolio theory, which assumes equilibrium and perfect ...

Many antineoplastics are designed to target upregulated genes, but quantifying upregulation in a single patient sample requires an appropriate set of samples for comparison. In cancer, the most ...

When we use simulation to estimate the performance of a stochastic system, the simulation often contains input models that were estimated from real-world data; therefore, there is both simulation and ...

Regular Bayesian and frequentist approximations in statistics are studied within a unified framework. In particular it is shown how some higher-order likelihood-based approximations arise from their ...