{"id":25437,"date":"2022-05-16T08:43:51","date_gmt":"2022-05-16T13:43:51","guid":{"rendered":"https:\/\/saluddigital.com\/?p=25437"},"modified":"2025-10-20T11:57:06","modified_gmt":"2025-10-20T17:57:06","slug":"la-inteligencia-artificial-podria-reducir-la-huella-de-carbono-relacionada-con-la-atencion-medica","status":"publish","type":"post","link":"https:\/\/saluddigital.com\/en\/big-data\/la-inteligencia-artificial-podria-reducir-la-huella-de-carbono-relacionada-con-la-atencion-medica\/","title":{"rendered":"Artificial Intelligence could reduce the carbon footprint related to health care"},"content":{"rendered":"
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Health care generates a large amount of greenhouse gas (GHG) emissions, when considering energy use for hospitals, heating, ventilation, construction, provider travel, medical staff and patients, among others.<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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Between the United States, Canada, Australia, and the United Kingdom, they emit ~7.5 \u00d7 10 14 grams (g) of carbon dioxide equivalent (CO 2 -eq) annually, in emissions related to healthcare services alone. In the world around 10% of all GHG emissions are due to health care processes, and everything that this entails, such as the development and transportation of pharmaceutical products or medical devices, use of technology, disposables, cleaning, and more .<\/p>

For this reason, Digital Health solutions such as telemedicine, which allows patients and doctors to avoid transfers to health centers, or Artificial Intelligence for medical decisions, are options for reducing emissions in the sector. The exponential growth of telemedicine during the pandemic made its advantages in reducing GHG emissions more evident.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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US researchers conducted an analysis that showed autonomous AI has the potential to reduce GHG emissions in healthcare by up to 80%. \u201cDigital health technology, and specifically telemedicine or telehealth, has the potential to improve patient care, the health of the population, reduce the per capita cost of medical care, and improve the experience of providing care,\u201d explains his article published in Nature.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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Likewise, the researchers highlight autonomous AI as another of the alternatives with great potential to improve the quality of medical care, especially when they are AI systems that perform tasks imitating the cognitive abilities of the human being. \u201cThese anthropomorphic AI systems are not explicitly programmed and instead learn from data to perform highly cognitive tasks, such as those typically performed by trained healthcare professionals,\u201d the authors explain.<\/p>

In this way, AI systems would have the potential to equalize access to medical care for populations that do not have health coverage.<\/p>

An example of autonomous AI that the authors expose is for the management and management of the health of a patient living with diabetes. The need for a full team of specialists, from primary care to eye care, requires separate clinic appointments. Autonomous AI, which has been recognized as a validated method, can be used to perform eye exams.<\/p>

Even the United States Food and Drug Administration (FDA) approved the first autonomous AI in 2018, precisely for eye exams for diabetic patients.<\/p>

\u201cAs the use of autonomous AI systems expands in the healthcare industry, measuring the real-world carbon emissions attributed to these systems compared to usual care will help elucidate the potential contributions of AI. autonomous in reducing emissions from health care,\u201d the authors conclude. You can consult the full study at the following link: https:\/\/www.nature.com\/articles\/s41746-022-00605-w<\/a><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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\n\t\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/i><\/span>\n\t\t\t\t\t\t\t\t<\/i><\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t BIBLIOGRAPHY<\/a>\n\t\t\t\t\t<\/div>\n\n\t\t\t\t\t

NATURE<\/strong><\/p>

https:\/\/www.nature.com\/articles\/s41746-022-00605-w<\/a><\/p><\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>","protected":false},"excerpt":{"rendered":"

La atenci\u00f3n m\u00e9dica genera una gran cantidad de emisiones de gases de efecto invernadero (GEI), al contemplar el uso de energ\u00eda para hospitales, calefacci\u00f3n, ventilaci\u00f3n, construcci\u00f3n, viajes de proveedores, personal m\u00e9dico y pacientes, entre otros. Entre Estados Unidos, Canad\u00e1, Australia y Reino Unido, emiten ~7.5 \u00d7 10 14 gramos (g) de di\u00f3xido de carbono equivalente (CO 2 -eq) anualmente, tan solo en emisiones relacionadas con los servicios de atenci\u00f3n m\u00e9dica. En el mundo alrededor del 10% de todas las emisiones GEI se deben a procesos de atenci\u00f3n de la salud, y todo lo que esta conlleva, como el desarrollo y transporte de productos farmac\u00e9uticos o dispositivos m\u00e9dicos, uso de tecnolog\u00eda, desechables, limpieza, y m\u00e1s. Por ello soluciones de Salud Digital como la telemedicina, que permite evitar traslados de pacientes y m\u00e9dicos a centros de salud, o la Inteligencia Artificial para la decisi\u00f3n m\u00e9dica, son opciones para la reducci\u00f3n de emisiones en el sector. El crecimiento exponencial de la telemedicina durante la pandemia hizo m\u00e1s evidentes sus ventajas en la reducci\u00f3n de emisiones de GEI. Investigadores estadounidenses realizaron un an\u00e1lisis que mostr\u00f3 que la IA aut\u00f3noma tiene el potencial de reducir las emisiones de GEI en atenci\u00f3n m\u00e9dica hasta en un 80%. \u201cLa tecnolog\u00eda de salud digital, y espec\u00edficamente la telemedicina o telesalud, tiene el potencial de mejorar la atenci\u00f3n al paciente, la salud de la poblaci\u00f3n, reducir el costo per c\u00e1pita de la atenci\u00f3n m\u00e9dica y mejorar la experiencia de brindar atenci\u00f3n\u201d, explica su art\u00edculo publicado en Nature. Asimismo, los investigadores destacan a la IA aut\u00f3noma, como otra de las alternativas con un gran potencial para mejorar la calidad en la atenci\u00f3n m\u00e9dica, sobre todo cuando son sistemas de IA que realizar tareas imitando capacidades cognitivas del ser humano. “Estos sistemas de IA antropom\u00f3rfica no est\u00e1n programados expl\u00edcitamente y, en cambio, aprenden de los datos para realizar tareas altamente cognitivas, como las que suelen realizar los profesionales de la salud capacitados”, explican los autores. De esta forma los sistemas de IA tendr\u00edan el potencial de igualar el acceso a la atenci\u00f3n m\u00e9dicas para poblaciones que no cuentan con cobertura de salud. Un ejemplo de IA aut\u00f3noma que exponen los autores es para la gesti\u00f3n y manejo de la salud de un paciente que vive con diabetes. La necesidad de un equipo completo de especialistas, desde la atenci\u00f3n primaria, hasta la atenci\u00f3n oftalmol\u00f3gica, requiere citas cl\u00ednicas por separado. Para realizar ex\u00e1menes oculares es posible utilizar la IA aut\u00f3noma, que se ha sido reconocida como un m\u00e9todo validado. Incluso la Administraci\u00f3n de Medicamentos y Alimentos de Estados Unidos (FDA), aprob\u00f3 la primera IA aut\u00f3noma en 2018, precisamente para ex\u00e1menes de vista para pacientes diab\u00e9ticos. “A medida que el uso de sistemas aut\u00f3nomos de IA se expande en la industria de la salud, la medici\u00f3n de las emisiones de carbono en el mundo real atribuidas a estos sistemas en comparaci\u00f3n con la atenci\u00f3n habitual ayudar\u00e1 a dilucidar las posibles contribuciones de la IA aut\u00f3noma en la reducci\u00f3n de las emisiones de la atenci\u00f3n m\u00e9dica”, concluyen los autores. Puedes consultar el estudio completo en el siguiente enlace: https:\/\/www.nature.com\/articles\/s41746-022-00605-w BIBLIOGRAF\u00cdA NATURE https:\/\/www.nature.com\/articles\/s41746-022-00605-w<\/p>","protected":false},"author":1,"featured_media":25439,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[156,3393,160],"tags":[145],"class_list":["post-25437","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-big-data","category-inteligencia-artificial-y-ciencia","category-noticias","tag-noticias"],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/posts\/25437","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/comments?post=25437"}],"version-history":[{"count":0,"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/posts\/25437\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/media\/25439"}],"wp:attachment":[{"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/media?parent=25437"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/categories?post=25437"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/tags?post=25437"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}