First, a random forest algorithm presents a model, the steps of which are described separately in Fig 1.
In this study, a predictive model for the diagnosis of heart disease was obtained using random forest and artificial neural network algorithms. The following is a description of the standard data, the proposed model, the model evaluation and the discussion and conclusion. With this model, it is possible to provide physicians with a decision-making system for diagnosing heart disease, which has the ability to differentiate the disease in the early stages and with high accuracy. The proposed model uses a combination of two random forest artificial network algorithms that have the desired accuracy for diagnosing heart disease. In 2018, Yahyaie and colleagues designed an article in an article entitled Using the Internet of Things to provide a new model for predicting remote heart attack using the Internet of Things (IoT), the output of which is valid when using ECG data. And by the rules of the association (AR), they designed a proposed algorithm whose output has a total classification accuracy of 98.96% and the time spent for classification is 94.94 seconds. published an article on optimizing particle density and supporting machine vectors optimized by association rules to identify the causes of heart disease using two particle density optimization (PSO) algorithms and SVM optimized support vector machine. Provides a number of patients for diagnosis and prognosis compared to RFS-IE and MRPS. designed a model to optimize the optimal criteria (OCFS) for the removal of inappropriate traits in an article titled an Optimal Criteria for Selection of Optimal Criteria Features for Predicting and Analyzing Effective Heart Disease Analysis (OCFS). UCI standard data were used for evaluation and the algorithm reached 90% accuracy for test data. It is responsible for the treatment of heart patients. This paper uses a combination of two genetic algorithms and a fuzzy logic algorithm. presented a paper to predict heart patients. And reached 81.19 percent accuracy for test data. In this study, first, the data were reduced to a dimensional scale, and then, with the help of a support vector machine with a radial base neural network kernel, a classification model was presented. presented a paper in a paper entitled "Dimensions reduction for the diagnosis of heart disease with the help of a supportive vector machine". It was found that the vector machine algorithm has the best output between the seven algorithms.
RANDOM FOREST VS NEURAL NETWORK SOFTWARE
Rapid Miner software was used in this study. In 2019, in a paper entitled as predictive model for cardiovascular disease forecasting, Perpra presented seven data mining algorithms. The following are some of the articles from the field. Designing assistive devices to help physicians diagnose the type of disease or choose the right type of treatment with the help of research can be a great help in saving lives. This extracted knowledge can be used as a decision-making system in the real world. In fact, the purpose of different stages of data mining is to discover knowledge and achieve results that can be used in the real world to improve efficiency. ĭata mining is very important in medical data. The use of heart prevention and detection methods can be of great help to physicians in diagnosing this disease. Mistakes in diagnosing the disease exacerbate the devastating effects and sometimes lead to death. Heart disease has negative effects on a person's life, making it impossible for them to do their daily activities. Early diagnosis of this disease plays an important role in a person's health and life.
Diagnosis of heart disease in the early stages is very important and necessary. Family and so on can cause heart disease. The heart acts like a pump and is responsible for pumping blood in the arteries of the human body if there are problems with how a person lives, stress, stress, unhealthy nutrition, inactivity and physical activity, having a history of heart disease.
The heart is an important part of the human body, and if you have a heart problem, you are more likely to die.
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