Applications of Artificial Intelligence in Cardiology. The Future is Already Here

[EN]There is currently no other hot topic like the ability of current technology to develop capabilities similar to those of human beings, even in medicine. This ability to simulate the processes of human intelligence with computer systems is known as artificial intelligence (AI). This article aims...

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Detalhes bibliográficos
Autores: Dorado Díaz, Pedro Ignacio, Sampedro-Gómez, Jesús, Vicente-Palacios, Víctor, Sánchez, Pedro L
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2019
País:España
Recursos:Universidad de Salamanca (USAL)
Repositorio:GREDOS. Repositorio Institucional de la Universidad de Salamanca
OAI Identifier:oai:gredos.usal.es:10366/161950
Acesso em linha:http://hdl.handle.net/10366/161950
Access Level:acceso abierto
Palavra-chave:Artificial intelligence
Machine learning
Deep learning
Cardiology
Inteligencia artificial
Cardiología
Cardiac Imaging Techniques
Humans
Algorithms
técnicas de imagen cardíaca
humanos
cardiología
algoritmos
Descrição
Resumo:[EN]There is currently no other hot topic like the ability of current technology to develop capabilities similar to those of human beings, even in medicine. This ability to simulate the processes of human intelligence with computer systems is known as artificial intelligence (AI). This article aims to clarify the various terms that still sound foreign to us, such as AI, machine learning (ML), deep learning (DL), and big data. It also provides an in-depth description of the concept of AI and its types; the learning techniques and technology used by ML; cardiac imaging analysis with DL; and the contribution of this technological revolution to classical statistics, as well as its current limitations, legal aspects, and initial applications in cardiology. To do this, we conducted a detailed PubMed search on the evolution of original contributions on AI to the various areas of application in cardiology in the last 5 years and identified 673 research articles. We provide 19 detailed examples from distinct areas of cardiology that, by using AI, have shown diagnostic and therapeutic improvements, and which will aid understanding of ML and DL methodology.