Decision tree

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Decision tree

A Decision tree (pronunciation: /dɪˈsɪʒən triː/) is a graphical representation of possible outcomes to a certain decision, based on various conditions. It is widely used in medicine, machine learning, and statistics to visualize complex decision-making processes.

Etymology

The term "decision tree" is derived from the tree-like structure of the diagram, which starts with a single node, then branches off into a number of solutions, just like a tree.

Definition

A decision tree is a flowchart-like structure in which each internal node represents a "test" on an attribute (e.g. whether a patient has a certain symptom), each branch represents the outcome of the test, and each leaf node represents a class label (decision taken after computing all attributes). The paths from root to leaf represent classification rules.

Use in Medicine

In medicine, decision trees can be used to guide the diagnostic process, treatment selection, and predicting patient outcomes. For example, a decision tree might be used to determine the best treatment plan for a patient with cancer based on their age, type of cancer, stage of cancer, and other health factors.

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