Future of cardiovascular diagnosis with the support of artificial intelligence

Abstract

Introduction: Term Artificial inteligence was used for the first time by John McCarthy in 1956, from that time we can observe its great development, espiecially in the past decade. Nowadays, Artificial inteligence present a great influence in every aspect of human life, also health care. In times of digitalizaton, great data bases it can enable an improvment in all aspects of healthcare system such as prevention, screening and treatment of diseases. Purpose:The main purpose of the work was to present the basic aspects related to artificial intelligence. Another important aspect of the article was to indicate the possibilities related to their use in cardiology to improve the effectiveness of doctors and make medical treatment more detailed and personalized, but also to clarify terms related do AI, such as machine learning or deep learning. Materials and methods: For the purpose of writing this article, the available literature was reviewed. Using keywords such as artificial inteligence, cardiology, machine learning, echocardiography, deep learning, data bases PubMed we ware searching for various clinical trials, meta analysis and randomized controlled trials from past 5 years. Results: According to the data published on the website of the World Health Organization (WHO), cardiovascular diseases remain the main cause of mortality worldwide. It is the reason of the great interest in its use in cardiology. Algorithms based on artificial intelligence are also used in electrocardiography. The use of artificial intelligence can improve the estimation of cardiovascular risk. Its use in the healing process is also being investigated. Conclusion: Artificial intelligence is used in many fields, including medicine. Its use may have a positive impact on the quality of medical care. Artificial intelligence also has numerous limitations. Due to this, it is necessary to develop and improve artificial intelligence.

Keywords

• artificial intelligence
• deep learning
• cardiology
• machine learning
• echocardiography