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There is a need to develop a system in order to collect patient data and make diagnoses based on them. These systems are generally called decision support systems. Decision support systems work by analyzing the data collected from the terminal units in accordance with the needs in the center to support decision making and presenting the results. Decision support systems can sometimes be developed for the field of health and sometimes for another field. Regardless of the field, the task of decision support systems is to infer with the help of the collected data and the rules at hand.

Decision support systems developed specifically for the health field are often referred to as clinical decision support systems. Clinical decision support systems sometimes help experts diagnose disease and recommend treatment methods based on health information. The concept of computer-aided clinical decision making came to the fore many years ago [15]. The working principle of clinical decision support systems is simply as follows: information such as blood values and enzyme values of the patient is obtained, this information is evaluated according to the knowledge base of the health institution, and an inference is made about the patient. When a direct relationship can be established between the inputs and the final decision during inference, this is known as an open box decision support system; when the correct relationship cannot be established between the inputs and the final decision, it is called a closed box decision support system [16].

A decision support system is a software that helps decision making and works based on the ruleset. The rule set can be in the form of simple IF-THEN rules or a more complex structure. Rule sets can be created with the help of expert knowledge or with models that learn from data. Comparing the event that occurred with the rules in the rule set determines which rule triggered the situation. Thus, whichever rule is triggered by the situation to produce the result, the output of the decision support system will be consistent.

Decision support systems are systems that help to decide about a situation. A system that will decide on HF takes the patient’s measurements as input and provides information about the risk of HF as output. The system’s inputs are sometimes the information coming from the IoT devices and sometimes the data that has been entered manually. For example, based on heart rate and blood values, it will be possible to predict whether there will be HF. At this point, we come across systems based on machine learning and knowledge. In machine learning based systems, data classification is carried out with the help of models trained with historical data. As a result of the classification, there might or might not be an indicated risk of HF.