This article presents a systematic mapping study dedicated to conduct a literature review on machine learning and IoT applied in the identification of diseases through heart sounds. This research was conducted between January 2010 and July 2021, considering IEEE Xplore, PubMed Central, ACM Digital Library, JMIR—Journal of Medical Internet Research, Springer Library, and Science Direct. The initial search resulted in 4372 papers, and after applying the inclusion and exclusion criteria, 58 papers were selected for full reading to answer the research questions. The main results are: of the 58 articles selected, 46 (79.31%) mention heart rate observation methods with wearable sensors and digital stethoscopes, and 34 (58.62%) mention care with machine learning algorithms. The analysis of the studies based on the bibliometric network generated by the VOSviewer showed in 13 studies (22.41%) a trend related to the use of intelligent services in the prediction of diagnoses related to cardiovascular disorders.

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Este artigo apresenta um mapeamento sistemático de trabalhos relacionados à aplicação de Internet das Coisas e Aprendizado de Máquina para realização de auscultação, com escopo na aquisição, processamento, análise da qualidade do sinal e apoio ao diagnóstico de disfunções cardiovasculares. Esta pesquisa abrange buscas de 2010 até julho de 2021 nas bases IEEE Xplore, PubMed Central, ACM Digital Library, JMIR - Journal of Medical Internet Research, Springer Library e Sciencedirect. A busca inicial resultou em 4.372 artigos e após aplicação dos critérios de inclusão e exclusão foram selecionados 58 artigos para leitura completa com o intuito de responder as questões de pesquisa. Os principais resultados são: dos 58 artigos selecionados foi constatado que 79,31% (46) citam métodos de observação de batimentos cardíacos com sensores vestíveis e estetoscópios digitais e 58,62% (34) fazem menção aos cuidados utilizando algoritmos de aprendizado de máquina. A análise do artigos demonstrou a tendência do uso de serviços inteligentes no diagnóstico de disjunções cardiovasculares.

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This article presents a systematic mapping study dedicated to conduct a literature review on machine learning and IoT applied in the identification of diseases through heart sounds. This research was conducted between January 2010 and July 2021, considering IEEE Xplore, PubMed Central, ACM Digital Library, JMIR- Journal of Medical Internet Research, Springer Library, and Science Direct. The initial search resulted in 4,372 papers, and after applying the inclusion and exclusion criteria, 58 papers were selected for full reading to answer the research questions. The main results are: of the 58 articles selected, 46 (79.31%) mention heart rate observation methods with wearable sensors and digital stethoscopes, and 34 (58.62%) mention care with machine learning algorithms. The analysis of the studies based on the bibliometric network generated by the VOSviewer showed in 13 studies (22.41%) a trend related to the use of intelligent services in the prediction of diagnoses related to cardiovascular disorders.