Bayes' theorem can modify evaluations of probability based on initial assumptions in the light of more data that later becomes available.

Concerning terrorism, we can express

Bayes' Theorem for the probability of identifying a terrorist using the TSA's new behavioral testing screen as follows:

Bayes' theorem can also be applied to the interpretation of clinical trials.

The methodology proposed in this article utilizes an expert judgment model within a Bayesian framework for the more complex case of continuous probability distributions, The most general form of

Bayes' Theorem applies to discrete probability distributions, and relates the conditional and prior probabilities of two events using the following equation,

This volume contains 10 chapters that review recently reported short interfering RNA (siRNA) design guidelines and clarifies the problems concerning the guidelines, as well as detailing an effective method for selecting siRNA target sequences from many possible candidate sequences using

Bayes' theorem, the development of a durable RNAi therapy for cancer and viral infections, and the structure, application, and therapeutic challenges of siRNA.

A naive Bayes classifier is a simple probabilistic classifier based on applying

Bayes' theorem with strong (naive) independence assumptions.

The BACS project is based on

Bayes' theorem, which provides a model for making rational judgements when the only information available is uncertain and incomplete.

Bayes' Theorem and the Epistemic Status of Competing Propositions

Crawley explains

Bayes' theorem in terms of conditional probability but omits the easier likelihood ratio approach, which is the form most used in medical diagnostics.

Bayes' theorem adds common sense to the maths used to work out how likely something is.

6) A simple statement of

Bayes' Theorem uses three terms.