Árbol de decisiones

Hello, my name is Ángel Adrián Falcón Molina, and I am a biomedical informatics instructor. Today, I'm going to talk to you about decision trees, which are the most popular tool for decision analysis. As you saw in the title, it's the decision tree. Here are the steps to create a decision tree: First, we have problem definition. The

better defined the problem, the clearer the alternatives will be. We'll develop a problem during the presentation. For example, I have 100 pesos to go out with a friend. Next, we'll identify alternatives. Remember that these should be the most important ones, and try not to oversimplify, as too many alternatives can become unhelpful. In our case, they should be

symbolized in a square. Continuing with our example, we have two alternatives: going to the movies or watching Netflix. Next, we have the outline of probable outcomes. These should also be the most important ones, and try not to oversimplify. Once again, this step should be symbolized in a circle. In our example, within the first

alternative, which is Netflix, we have two Possible outcomes: spending money on pizza and saving money. We also have two other possible outcomes: going out again and buying a new sweater. In our alternative of going to the movies, we have two probable outcomes: spending money on transportation and spending money on candy. However, we also have two more

probable outcomes: getting robbed or not. The next step is assigning probabilities to each outcome. It's important to remember that in medicine, this information should be obtained from the most reliable sources, such as expert opinion. The sum of the percentages for each outcome must always equal 100%, or 1. In our case, let's imagine we obtained