{"id":8343,"date":"2020-10-09T09:23:28","date_gmt":"2020-10-09T09:23:28","guid":{"rendered":"https:\/\/www.kolabtree.com\/blog\/?p=8343"},"modified":"2020-12-04T11:06:37","modified_gmt":"2020-12-04T11:06:37","slug":"applications-of-data-analytics-in-healthcare","status":"publish","type":"post","link":"https:\/\/www.kolabtree.com\/blog\/pt\/applications-of-data-analytics-in-healthcare\/","title":{"rendered":"Aplica\u00e7\u00f5es da an\u00e1lise de dados na \u00e1rea da sa\u00fade"},"content":{"rendered":"<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_45_1 counter-flat ez-toc-counter ez-toc-grey ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title\">Tabela de Conte\u00fados<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" area-label=\"ez-toc-toggle-icon-1\"><label for=\"item-69f141c8573cb\" aria-label=\"Table of Content\"><span style=\"display: flex;align-items: center;width: 35px;height: 30px;justify-content: center;direction:ltr;\"><svg style=\"fill: #999;color:#999\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewbox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #999;color:#999\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewbox=\"0 0 24 24\" version=\"1.2\" baseprofile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/label><input  type=\"checkbox\" id=\"item-69f141c8573cb\"><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1' ><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/www.kolabtree.com\/blog\/pt\/applications-of-data-analytics-in-healthcare\/#Applications_of_data_science_in_healthcare\" title=\"Aplica\u00e7\u00f5es da ci\u00eancia dos dados na sa\u00fade\">Aplica\u00e7\u00f5es da ci\u00eancia dos dados na sa\u00fade<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/www.kolabtree.com\/blog\/pt\/applications-of-data-analytics-in-healthcare\/#Drug_Discovery\" title=\"Descoberta de drogas\">Descoberta de drogas<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/www.kolabtree.com\/blog\/pt\/applications-of-data-analytics-in-healthcare\/#Disease_Prevention\" title=\"Preven\u00e7\u00e3o de doen\u00e7as\">Preven\u00e7\u00e3o de doen\u00e7as<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/www.kolabtree.com\/blog\/pt\/applications-of-data-analytics-in-healthcare\/#Diagnosis_and_Treatment\" title=\"Diagn\u00f3stico e tratamento\">Diagn\u00f3stico e tratamento<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/www.kolabtree.com\/blog\/pt\/applications-of-data-analytics-in-healthcare\/#Post-Care_Monitoring\" title=\"Monitoramento P\u00f3s-atendimento\">Monitoramento P\u00f3s-atendimento<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/www.kolabtree.com\/blog\/pt\/applications-of-data-analytics-in-healthcare\/#Hospital_Operations\" title=\"Opera\u00e7\u00f5es hospitalares\">Opera\u00e7\u00f5es hospitalares<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/www.kolabtree.com\/blog\/pt\/applications-of-data-analytics-in-healthcare\/#The_future_of_data_science_in_healthcare\" title=\"O futuro da ci\u00eancia dos dados na sa\u00fade\">O futuro da ci\u00eancia dos dados na sa\u00fade<\/a><\/li><\/ul><\/nav><\/div>\n<p><em>Nikita N., freelance scientific writer on Kolabtree, outlines the top applications of data analytics in <a href=\"https:\/\/www.kolabtree.com\/blog\/pt\/ensuring-reproducibility-in-ai-driven-research-how-freelance-experts-can-help-in-biotech-and-healthcare\/\">sa\u00fade<\/a>.\u00a0<\/em><\/p>\n<p><span style=\"font-weight: 400;\">O termo \"An\u00e1lise de dados\" \u00e9 a pr\u00e1tica de acumular grandes quantidades de dados, os quais s\u00e3o analisados e os insights essenciais s\u00e3o extra\u00eddos das informa\u00e7\u00f5es contidas. Hoje em dia, novos softwares e tecnologias facilitam o exame de grandes volumes de dados para detalhes ocultos.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Nos \u00faltimos tempos, a ind\u00fastria da sa\u00fade tem se tornado cada vez mais exigente. O aumento do n\u00famero de pacientes dificultou a administra\u00e7\u00e3o eficiente do trabalho por parte dos m\u00e9dicos e do pessoal. De acordo com um relat\u00f3rio de an\u00e1lise da McKinsey, as despesas com a sa\u00fade nos EUA s\u00e3o <\/span><a href=\"https:\/\/www.statista.com\/statistics\/184968\/us-health-expenditure-as-percent-of-gdp-since-1960\/\"><span style=\"font-weight: 400;\">17.6%<\/span><\/a><span style=\"font-weight: 400;\"> do PIB, que \u00e9 quase $600 bilh\u00f5es a mais do que o valor de refer\u00eancia da riqueza e tamanho dos Estados Unidos. Com o aumento de tais necessidades, a an\u00e1lise de dados pode servir como uma solu\u00e7\u00e3o promissora para resolver problemas na ind\u00fastria da sa\u00fade. De acordo com a an\u00e1lise de mercado, espera-se que o setor de an\u00e1lise de dados seja mais de <\/span><a href=\"https:\/\/healthitanalytics.com\/news\/deep-learning-blockchain-big-data-to-see-huge-growth-in-healthcare\"><span style=\"font-weight: 400;\">$68.03<\/span><\/a><span style=\"font-weight: 400;\"> bilh\u00f5es at\u00e9 2024. Os setores-alvo da sa\u00fade onde a an\u00e1lise de dados pode trazer uma mudan\u00e7a significativa incluem a descoberta de medicamentos, preven\u00e7\u00e3o de doen\u00e7as, diagn\u00f3stico, tratamento, monitoramento p\u00f3s-tratamento, opera\u00e7\u00f5es hospitalares.\u00a0<\/span><\/p>\n<h2><span class=\"ez-toc-section\" id=\"Applications_of_data_science_in_healthcare\"><\/span>Aplica\u00e7\u00f5es da ci\u00eancia dos dados na sa\u00fade<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<h3><span class=\"ez-toc-section\" id=\"Drug_Discovery\"><\/span><strong>Descoberta de drogas<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><span style=\"font-weight: 400;\">Geralmente, o processo de descoberta de drogas leva muito tempo, cerca de 12 anos, e custa muito, cerca de <\/span><a href=\"https:\/\/www.policymed.com\/2014\/12\/a-tough-road-cost-to-develop-one-new-drug-is-26-billion-approval-rate-for-drugs-entering-clinical-de.html\"><span style=\"font-weight: 400;\">$2,6 bilh\u00f5es<\/span><\/a><span style=\"font-weight: 400;\">. A an\u00e1lise de dados aumenta a taxa do processo de entrega de medicamentos na ci\u00eancia m\u00e9dica, ajudando a obter uma aprova\u00e7\u00e3o mais r\u00e1pida na Administra\u00e7\u00e3o de Alimentos e Medicamentos e curando os pacientes mais rapidamente. <\/span><span style=\"font-weight: 400;\">Algumas empresas est\u00e3o desenvolvendo m\u00e1quinas artificiais inteligentes para aplica\u00e7\u00f5es em v\u00e1rios setores. Por exemplo, a empresa BenevolentAI desenvolveu diferentes dispositivos inteligentes artificiais, tais como um <\/span><a href=\"https:\/\/www.prnewswire.com\/news-releases\/benevolentai-raises-115-million-to-extend-its-leading-global-position-in-the-field-of-ai-enabled-drug-development-680180573.html\"><span style=\"font-weight: 400;\">c\u00e9rebro de m\u00e1quina biocient\u00edfica<\/span><\/a><span style=\"font-weight: 400;\"> e outros algoritmos modelo para criar novos medicamentos para doen\u00e7as dif\u00edceis de tratar. A organiza\u00e7\u00e3o \u00e9 um exemplo de uma empresa de AI totalmente integrada com desenvolvimento cl\u00ednico e capacidade de descoberta farmac\u00eautica. A tecnologia revoluciona as ind\u00fastrias farmac\u00eauticas, diminuindo os custos, diminuindo as taxas de falhas e entregando medicamentos aos pacientes em um ritmo mais r\u00e1pido.\u00a0<\/span><\/p>\n<h3><span class=\"ez-toc-section\" id=\"Disease_Prevention\"><\/span><strong>Preven\u00e7\u00e3o de doen\u00e7as<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><span style=\"font-weight: 400;\">A an\u00e1lise de dados previne doen\u00e7as atrav\u00e9s do reconhecimento precoce dos riscos, e as ferramentas tamb\u00e9m recomendam planos preventivos. V\u00e1rios dispositivos inteligentes que utilizam a an\u00e1lise de dados utilizam as informa\u00e7\u00f5es gen\u00e9ticas e os padr\u00f5es hist\u00f3ricos das pessoas para reconhecer os problemas antes que eles saiam do controle.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">V\u00e1rias empresas est\u00e3o desenvolvendo dispositivos inteligentes que utilizam a an\u00e1lise de dados para analisar os v\u00e1rios planos de comportamento dos pacientes em um est\u00e1gio inicial, o que pode ajudar a prevenir doen\u00e7as como condi\u00e7\u00f5es cr\u00f4nicas de sa\u00fade, como diabetes, hipertens\u00e3o e colesterol alto em um est\u00e1gio inicial.\u00a0<\/span><\/p>\n<h3><span class=\"ez-toc-section\" id=\"Diagnosis_and_Treatment\"><\/span><strong>Diagn\u00f3stico e tratamento<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><span style=\"font-weight: 400;\">Outra aplica\u00e7\u00e3o \u00fatil da ci\u00eancia de dados em sa\u00fade \u00e9 a imagiologia m\u00e9dica, na qual os algoritmos interpretam eficientemente <\/span><span style=\"font-weight: 400;\">Raios-X, MRIs, mamografias e outros tipos de imagens, o que ajuda na identifica\u00e7\u00e3o de padr\u00f5es nos dados e detec\u00e7\u00e3o de tumores, anomalias de \u00f3rg\u00e3os, estenose arterial mais clara. <\/span><span style=\"font-weight: 400;\">\u00a0Modelos de algoritmos de an\u00e1lise de dados podem diagnosticar ritmos card\u00edacos irregulares<\/span><span style=\"font-weight: 400;\"> de ECGs mais r\u00e1pido que um cardiologista e distinguir claramente entre imagens de les\u00f5es malignas e marcas de pele benignas.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">O tratamento atual na \u00e1rea da sa\u00fade tornou-se mais confort\u00e1vel com a disponibilidade de mais dados sobre as caracter\u00edsticas individuais do paciente, permitindo a entrega de dados mais precisos de prescri\u00e7\u00e3o e atendimento personalizado. A ci\u00eancia dos dados est\u00e1 melhorando o campo emergente da terapia gen\u00e9tica. A inser\u00e7\u00e3o de material gen\u00e9tico nas c\u00e9lulas e a substitui\u00e7\u00e3o de medicamentos tradicionais \u00e9 mais control\u00e1vel do que antes.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Empresas de consultoria anal\u00edtica como <\/span><a href=\"https:\/\/www.bain.com\/vector-digital\/advanced-analytics\/%C2%A0\"><span style=\"font-weight: 400;\">Banho<\/span><\/a><span style=\"font-weight: 400;\"> ou <\/span><a href=\"https:\/\/www.scnsoft.com\/services\/analytics\/consulting\"><span style=\"font-weight: 400;\">ScienceSoft<\/span><\/a><span style=\"font-weight: 400;\"> pode desenvolver software anal\u00edtico de dados para v\u00e1rios setores, incluindo o setor de sa\u00fade.\u00a0 <\/span><span style=\"font-weight: 400;\">Existe uma falta de comunica\u00e7\u00e3o entre as consultas e a falta de envolvimento dos pacientes com v\u00e1rias doen\u00e7as cr\u00f4nicas, como diabetes, asma, doen\u00e7as cardiovasculares. O software recebido do EHR e de um paciente, analisa os dados de sa\u00fade e altera os membros da equipe de atendimento ou os pacientes para solu\u00e7\u00f5es eficazes. \u00c9 o software <\/span><span style=\"font-weight: 400;\">e um aplicativo de desktop integrado ao EMR permitem saber se o medicamento prescrito entra em conflito com a condi\u00e7\u00e3o e a doen\u00e7a atual do paciente.<\/span><span style=\"font-weight: 400;\"> O software de an\u00e1lise de dados ajuda a gerenciar os custos, acompanhando as despesas de tratamento da condi\u00e7\u00e3o ao longo de todo o ciclo de cuidados. Ele encontra oportunidades para reduzir substancialmente os custos sem afetar negativamente os resultados, e compara os custos de cuidar de uma condi\u00e7\u00e3o com os resultados<\/span><span style=\"font-weight: 400;\">. <\/span><\/p>\n<blockquote><p><span style=\"font-weight: 400;\">Empresas como a NextBio est\u00e3o desenvolvendo modelos anal\u00edticos de dados para personalizar tamb\u00e9m o tratamento do paciente e fornecer mais op\u00e7\u00f5es dispon\u00edveis, examinando dados cl\u00ednicos e gen\u00f4micos anteriores. Por exemplo, a radioterapia \u00e9 a \u00fanica forma de tratamento para pacientes com c\u00e2ncer. Os modelos anal\u00edticos de dados fornecem tratamento personalizado e oferecem m\u00e9todos alternativos de tratamento.\u00a0<\/span><\/p><\/blockquote>\n<h3><span class=\"ez-toc-section\" id=\"Post-Care_Monitoring\"><\/span><strong>Monitoramento P\u00f3s-atendimento<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><span style=\"font-weight: 400;\">Outra \u00e1rea onde a an\u00e1lise de dados encontra aplica\u00e7\u00f5es interessantes \u00e9 para o tratamento de pacientes domiciliares. Geralmente, ap\u00f3s cirurgias, os pacientes reclamam de complica\u00e7\u00f5es e dores recorrentes, o que \u00e9 dif\u00edcil para os m\u00e9dicos quando saem do hospital. A aplica\u00e7\u00e3o da an\u00e1lise de dados no monitoramento remoto em casa facilita o contato dos m\u00e9dicos com os pacientes. Portanto, reduzindo a necessidade de recursos hospitalares caros. Por exemplo, com base nos dados do EMR, <\/span><span style=\"font-weight: 400;\">Os hospitais podem prever quando os pacientes precisariam ser readmitidos nos pr\u00f3ximos 30 dias,\u00a0<\/span><\/p>\n<h3><span class=\"ez-toc-section\" id=\"Hospital_Operations\"><\/span><strong>Opera\u00e7\u00f5es hospitalares<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><span style=\"font-weight: 400;\">A an\u00e1lise de dados ajuda a aumentar a for\u00e7a de trabalho dos funcion\u00e1rios nos hospitais, atribuindo-lhes certas horas, garantindo a disponibilidade de leitos hospitalares suficientes, aumentando a utiliza\u00e7\u00e3o na sala de cirurgia. Outra ferramenta de an\u00e1lise de dados, ou seja, a an\u00e1lise preditiva, pode otimizar a programa\u00e7\u00e3o.\u00a0<\/span><\/p>\n<h2><span class=\"ez-toc-section\" id=\"The_future_of_data_science_in_healthcare\"><\/span><strong>O futuro da ci\u00eancia dos dados na sa\u00fade<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Assim como toda ind\u00fastria, o uso da ci\u00eancia de dados na sa\u00fade tem seus pr\u00f3s e seus contras. Os dados nos hospitais e unidades administrativas est\u00e3o geralmente em um estado desesperado. \u00c9 um desafio integrar a an\u00e1lise de dados no sistema de sa\u00fade. Os pacientes est\u00e3o preocupados com a privacidade e a prote\u00e7\u00e3o de suas informa\u00e7\u00f5es de sa\u00fade.<\/span><span style=\"font-weight: 400;\">. N\u00e3o h\u00e1 d\u00favida de que a ci\u00eancia dos dados pode resolver a escassez de m\u00e9dicos. Entretanto, muitas pessoas est\u00e3o preocupadas em perder a rela\u00e7\u00e3o paciente-m\u00e9dico com os algoritmos de computador. <\/span><span style=\"font-weight: 400;\">No entanto, espera-se que a am\u00e1lgama de an\u00e1lise de dados e sa\u00fade cres\u00e7a nos pr\u00f3ximos anos.<\/span><span style=\"font-weight: 400;\"> A an\u00e1lise de mercado revela que a an\u00e1lise de dados na \u00e1rea da sa\u00fade alcan\u00e7ar\u00e1 <\/span><a href=\"http:\/\/www.abnewswire.com\/pressreleases\/big-data-in-healthcare-2017-global-market-to-reach-us-3427-billion-and-growing-at-cagr-of-2207-by-2022_149937.html\"><span style=\"font-weight: 400;\">$34,27 bilh\u00f5es<\/span><\/a><span style=\"font-weight: 400;\"> at\u00e9 2022 em um CAGR de 22.07%.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">De fato, a ci\u00eancia dos dados \u00e9 uma via para melhorar a qualidade do setor de sa\u00fade por ter aplica\u00e7\u00f5es no diagn\u00f3stico precoce de doen\u00e7as, imagens m\u00e9dicas, descoberta mais r\u00e1pida de medicamentos e manuseio de opera\u00e7\u00f5es hospitalares complexas tamb\u00e9m em \u00e1reas rurais, ajudando a curar doen\u00e7as significativas como AIDS, c\u00e2ncer e \u00e9bola.\u00a0<\/span><\/p>\n<p><strong>Necessidade de contratar um analista de dados de sa\u00fade? Veja<a href=\"https:\/\/www.kolabtree.com\/find-an-expert\/subject\/health-data-analysis\/?utm_source=Blog&amp;utm_medium=Post&amp;utm_campaign=DA-Healthcare\"> analistas de dados de sa\u00fade<\/a> em Kolabtree ou poste seu projeto gratuitamente. <a href=\"https:\/\/www.kolabtree.com\/create-project\/?utm_source=Blog&amp;utm_medium=Post&amp;utm_campaign=DA-Healthcare\">POSTAR UM PROJETO AGORA<\/a><\/strong><\/p>","protected":false},"excerpt":{"rendered":"<p>Nikita N., freelance scientific writer on Kolabtree, outlines the top applications of data analytics in healthcare.\u00a0 The term \u201cData analytics\u201d is the practice of accumulating vast quantities of data, which are analyzed and essential insights are drawn from the information contained. Nowadays, new software and technologies make it easier to examine large volumes of data<\/p>\n<div class=\"read-more\"><a href=\"https:\/\/www.kolabtree.com\/blog\/pt\/applications-of-data-analytics-in-healthcare\/\" title=\"Leia mais\">Leia mais<\/a><\/div>","protected":false},"author":12,"featured_media":8403,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[434,398,443,653,433],"tags":[180,651],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v20.1 (Yoast SEO v20.1) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Applications of Data Analytics in Healthcare - The Kolabtree Blog<\/title>\n<meta name=\"description\" content=\"From drug discovery to more accurate diagnoses, the top applications of data analytics in healthcare.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.kolabtree.com\/blog\/pt\/applications-of-data-analytics-in-healthcare\/\" \/>\n<meta property=\"og:locale\" content=\"pt_BR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Applications of Data Analytics in Healthcare\" \/>\n<meta property=\"og:description\" content=\"From drug discovery to more accurate diagnoses, the top applications of data analytics in healthcare.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.kolabtree.com\/blog\/pt\/applications-of-data-analytics-in-healthcare\/\" \/>\n<meta property=\"og:site_name\" content=\"The Kolabtree Blog\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/kolabtree\" \/>\n<meta property=\"article:published_time\" content=\"2020-10-09T09:23:28+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2020-12-04T11:06:37+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.kolabtree.com\/blog\/wp-content\/uploads\/2020\/09\/health-data-analyst.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"626\" \/>\n\t<meta property=\"og:image:height\" content=\"417\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"Ramya Sriram\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@kolabtree\" \/>\n<meta name=\"twitter:site\" content=\"@kolabtree\" \/>\n<meta name=\"twitter:label1\" content=\"Escrito por\" \/>\n\t<meta name=\"twitter:data1\" content=\"Ramya Sriram\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. tempo de leitura\" \/>\n\t<meta name=\"twitter:data2\" content=\"5 minutos\" \/>\n<!-- \/ Yoast SEO Premium plugin. -->","yoast_head_json":{"title":"Applications of Data Analytics in Healthcare - 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