The fundamental information theory functions of entropy, relative entropy, and mutual
information are directly applicable to clinical diagnostic testing. This is a consequence of the …

Since 1948, Shannon theoretic methods for modeling information have found a wide range
of applications in several areas where information plays a key role, which goes well beyond …

The goal of obtaining information to improve classification accuracy can strongly conflict with
the goal of obtaining information for improving payoffs. Two environments with such a …

Agreement measures are useful tools to both compare different evaluations of the same
diagnostic outcomes and validate new rating systems or devices. Cohen's kappa (κ) …

Background Clinical workflow is infused with large quantities of data, particularly in areas
with enhanced monitoring such as the Intensive Care Unit (ICU). Information theory can …

Objective To precisely define the utility of tests in a clinical pathway through data-driven
analysis of the electronic medical record (EMR). Materials and methods The information …

We apply the information theory concept of “channel capacity” to diagnostic test performance
and derive an expression for channel capacity in terms of test sensitivity and test specificity …

Background Narrative medical reports do not use standardized terminology and often bring
insufficient information for statistical processing and medical decision making. Objectives of …

The goal of this work is to present information theory, specifically Claude Shannon's
mathematical theory of communication, in a clinical context and elucidate its potential …

The information-theoretic concept of Shannon entropy can be used to quantify the
information provided by a diagnostic test. We hypothesized that in tumor types with …