Decision Analysis is an easily-extensible expert system to help users make decisions of all types. Written entirely in Python, Decision Analysis, at this time, contains a general decsion module, which uses a weighted average technique to evaluate use
The application of explicit, quantitative methods that quantify prognoses, treatment effects, and patient values in order to analyse a decision under conditions of uncertainty.
is the application of explicit, quantitative methods to analyse decisions under conditions of uncertainty.
an approach to decision making under conditions of uncertainty that involves modeling of the sequences or pathways of multiple possible strategies (e.g., of diagnosis and treatment for a particular clinical problem) to determine which is optimal. It is based upon available estimates (drawn from the literature or from experts) of the probabilities that certain events and outcomes will occur and the values of the outcomes that would result from each strategy. A decision tree is a graphical representation of the alternate pathways.
A methodology for making decisions by identifying alternatives and assessing them with regard to both the likelihood of possible outcomes and the costs and benefits of the outcomes.
An explicit, quantitative approach for prescribing decisions under conditions of uncertainty.
A technique that formally identifies the options in a decision-making process, quantifies the probable outcomes (and costs) of each, determines the option that best meets the objectives of the decision-maker and assesses the robustness of this conclusion.
A formal model for describing and analyzing a decision; also called medical decision-making.
Decision Analysis (DA) is the discipline comprising the philosophy, theory, methodology, and professional practice necessary to address important decisions in a formal manner. Decision analysis includes many procedures, methods, and tools for identifying, clearly representing, and formally assessing the important aspects of a decision situation, for computing the recommended course of action by applying the maximum expected utility action axiom to a well-formed representation of the decision, and for translating the formal representation of a decision and its corresponding recommendation into insight for the decision-maker and other decision participants.
