Real-world data (RWD) derived from electronic health records (EHRs) are often used to understand population-level relationships between patient characteristics and cancer outcomes. Machine learning ...
Systematic Biology, Vol. 64, No. 1, SPECIAL ISSUE: MATHEMATICAL AND COMPUTATIONAL EVOLUTIONARY BIOLOGY (2013) (JANUARY 2015), pp. 66-83 (18 pages) Species tree methods are now widely used to infer the ...
Our foray into causal analysis is not yet complete. Until we define the methods of causal inference, we can't get to the deeper insights that causal analysis can provide. This article details many of ...
In the quest to unravel the underlying mechanisms of natural systems, accurately identifying causal interactions is of paramount importance. Leveraging the advancements in time-series data collection ...
In the article that accompanies this editorial, Lu et al 5 conducted a systematic review on the use of instrumental variable (IV) methods in oncology comparative effectiveness research. The main ...
The majority of recent empirical papers in operations management (OM) employ observational data to investigate the causal effects of a treatment, such as program or policy adoption. However, as ...
The application of Bayesian methods to large-scale phylogenetics problems is increasingly limited by computational issues, motivating the development of methods that can complement existing Markov ...
AI inference uses trained data to enable models to make deductions and decisions. Effective AI inference results in quicker and more accurate model responses. Evaluating AI inference focuses on speed, ...
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