Glossary of Terms

Analytical Error: The measurement error of an analytical process.

Analytical Performance Specifications: Quantitative criteria that specify the required quality of analytical performance necessary to deliver laboratory test information that meets clinical needs and improves health outcomes.

Bayesian: Statistical methods based on Bayes' theorem, incorporating prior knowledge or beliefs into probability calculations.

Bayes' Theorem: A fundamental theorem in probability theory that relates the conditional probability P(H|E) of a hypothesis H beeing true given the evidence E to the likelihood P(E|H) of observing evidence E given the hypothesis H is true, along with the prior probability of H.

Clinical: Related to the diagnosis and treatment of patients.

Complex Systems: Systems composed of interconnected parts that exhibit emergent properties and behaviors not readily predictable from the properties of individual components. They may be sensitive to initial conditions and can display chaotic behavior.

Critical Failure: A failure that can initiate hazard.

Diagnostic Accuracy: A measure of how well a diagnostic test correctly identifies or excludes a condition, characterized by its sensitivity and specificity.

Entropy: A measure of the disorder or randomness in a system, often associated with the number of microscopic configurations corresponding to a thermodynamic system's macroscopic state.

Failure: The termination of an item's ability to perform a required function.

Genetic Algorithms: Optimization algorithms inspired by natural selection and genetics, utilizing operators like selection, crossover, and mutation to evolve solutions. They work with populations of candidate solutions encoded as strings, analogous to DNA or RNA strands, effectively exploring large and complex search spaces.

Hazard: The potential source of harm.

Medical Diagnosis: The probabilistic mapping of symptoms, signs, and findings from laboratory tests and medical imaging onto a specific disease condition using medical knowledge.

Measurement Uncertainty: A parameter associated with the result of a measurement that characterizes the range of the values that could reasonably be attributed to the measurand.

Negative Predictive Value: The proportion of individuals with a negative diagnostic test who are actually nondiseased.

Network: A graph representation of a system where nodes (vertices) represent the system's components and edges represent their relationships.

Neural Networks: Computational models inspired by the human brain's structure and function, consisting of interconnected nodes (neurons) that process information in layers to perform tasks like pattern recognition, data classification, and regression.

Numerical Methods: Techniques and algorithms used to obtain approximate solutions to mathematical problems that may be difficult or impossible to solve analytically.

Optimization: The process of selecting the best alternative among several options, typically involving the maximization or minimization of an objective function based on the system's goals.

Positive Predictive Value: The proportion of individuals with a positive diagnostic test who are diseased.

Prevalence: The proportion of a population that has a particular disease or attribute in a given time period.

Probability Density Function: A function that describes the likelihood of a continuous random variable taking on a particular value; the area under the PDF over an interval represents the probability that the variable falls within that interval.

Quality Control: Statistical methods used to understand, monitor, and improve a process or product.

Receiver Operating Characteristic (ROC) Plots (Curves): Graphical plots illustrating the diagnostic ability of a diagnostic test by plotting the true positive rate (sensitivity) against the false positive rate (1 − specificity) at various threshold settings.

Reliability: The probability that an item will perform a required function under stated conditions for a stated period.

Residual Risk: The risk remaining after the control measures have been implemented.

Risk: A combination of the probability of occurrence of harm and the severity of that harm due to a hazard.

Risk Management: The practice of analyzing, evaluating, controlling, and monitoring risk.

Sensitivity: The proportion of diseased individuals who have a positive diagnostic test.

Simulation: The process of modeling a real-world system using computational models to study its behavior under various conditions.

Specificity: The proportion of nondiseased individuals who have a negative diagnostic test.

Symbolic Computation: The mathematical transformation of symbolic expressions using computer algorithms.

Uncertainty: An expression of imperfect or deficient information; when quantifiable, it can be represented by probability.

Unincorporated Association: Two or more persons bound together for one or more common purposes, not being business purposes, by mutual undertakings, each having mutual duties and obligations, in an organisation which has rules which identify in whom control of it and its funds rests and upon what terms and which can be joined or left at will.

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