Decades ago, Paul Erdős used randomness to illuminate the vast and weird world of networks. Now mathematicians are making his ...
Imagine a scenario where a team of doctors faces a perplexing medical puzzle. A patient shows a range of symptoms, each pointing to multiple possible diseases. How can they navigate this diagnostic ...
A representation of the cause-effect mechanism is needed to enable artificial intelligence to represent how the world works. Bayesian Networks (BNs) have proven to be an effective and versatile tool ...
Abstract: Assessing the failure of urban gas pipelines is crucial for identifying risk factors and preventing gas accidents that result in economic losses and casualties. Most previous studies on gas ...
Implementation of Bayesian Network Based on Ultra-High-Speed Superconductor Random Number Generators
Abstract: A Bayesian network (BN) is a graphical model that represents causal relationships between events. BNs have been widely used in applications such as forecasting, diagnosis, and classification ...
Trials of surgical evacuation of supratentorial intracerebral hemorrhages have generally shown no functional benefit. Whether early minimally invasive surgical removal would result in better outcomes ...
Inference of gene flow using genomic data requires powerful methods as the process of coalescent, migration, and mutation is highly stochastic. However, it is challenging to implement the multispecies ...
Reporting guidelines are listed on The EQUATOR Network website, which maintains a comprehensive collection of guidelines and other materials related to health research reporting. 77 Table 1 shows ...
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