Abstract
Heart disease is the leading cause of death from chronic diseases in the developing countries. The difficulty of making an accurate and timely diagnosis is exacerbated by a lack of resources and professionals in some areas, which contributes to this reality. Medical professionals may benefit from technological advancements that aid in the accurate diagnosis of patients. In light of these findings, a hybrid diagnostic tool has been developed that combines several computational intelligence (machine learning) techniques capable of analyzing clinical histories and images of electrocardiogram signals and indicating whether or not the patient has ischemic heart disease with up to 97.01% accuracy. Working with medical experts and a database containing clinical data on approximately 1020 patients and their diagnoses was required for this project. Both were put to use. A picture database containing 92 images of electrocardiogram signals was also used in this project for the analysis of the Artificial Neural Network. After extensive research and testing by the medical community, which supported the project and provided positive feedback, a successful tool was developed. This demonstrated the tool's effectiveness.
Highlights
The relevance of the issue described here [1] is increased by the intricacy and importance of medical diagnosis, which can lead to disastrous outcomes if errors are made
The main objective of Applied Bionics and Biomechanics this work is to propose the development of a hybrid tool, where it is possible to record the experiences of medical specialists, especially those related to the studied domain, later allowing the system to use this knowledge to solve future problems through application of artificial intelligence techniques (Case-Based Recognition, Genetic Algorithms, and Artificial Neural Networks)
An average error curve similar to that shown in Figure 1 can be observed, which corresponds to the result of the Artificial Neural Networks (ANN) training process, for diagnosis of ischemic heart disease based on clinical data, that is, without performing any analysis on the images of the ECG signals
Summary
The relevance of the issue described here [1] is increased by the intricacy and importance of medical diagnosis, which can lead to disastrous outcomes if errors are made. There is a shortage of experts in various specialties in various areas, and no doctor, no matter how talented, is capable of attending to all specialties These characteristics contribute to a favourable environment for the development and dissemination of intelligent tools that can help to decrease the complexity of diagnostic work, resulting in a number of benefits for society as a whole [2]. The main objective of Applied Bionics and Biomechanics this work is to propose the development of a hybrid tool, where it is possible to record the experiences of medical specialists, especially those related to the studied domain (ischemic heart disease), later allowing the system to use this knowledge to solve future problems through application of artificial intelligence techniques (Case-Based Recognition, Genetic Algorithms, and Artificial Neural Networks)
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