{"id":23782,"date":"2022-02-01T08:27:21","date_gmt":"2022-02-01T14:27:21","guid":{"rendered":"https:\/\/saluddigital.com\/?p=23782"},"modified":"2025-10-21T10:23:03","modified_gmt":"2025-10-21T16:23:03","slug":"la-inteligencia-artificial-podria-mejorar-el-acceso-a-servicios-de-salud-mental","status":"publish","type":"post","link":"https:\/\/saluddigital.com\/en\/big-data\/la-inteligencia-artificial-podria-mejorar-el-acceso-a-servicios-de-salud-mental\/","title":{"rendered":"Artificial Intelligence could improve access to mental health services"},"content":{"rendered":"
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Researchers from MIT and Massachusetts General Hospital (MGH) propose the use of machine learning and Artificial Intelligence (AI) to improve access to mental health care services.<\/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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MIT researchers suggest that AI may be able to help make mental health services more accessible to patients. The psychologist and researcher Paola Pedrelli, from the MGH, explained that, from her experience, she has encountered various barriers to accessing mental health, including when and where to seek help.<\/p>

In this sense, Pedrelli, in collaboration with MIT researcher Rosalind Picard, have worked for the last five years on a project based on machine learning algorithms, which seeks to help diagnose and monitor symptoms in patients with depression.<\/p>

\u201cWe are trying to build sophisticated models that have the ability not only to learn what is common between people, but also to learn categories of what is changing in an individual's life,\u201d Picard explained. In addition, he highlighted that they seek to provide people with the opportunity to access personalized information based on evidence that really makes a difference in their health.<\/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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The researchers conducted an initial study of MGH participants with major depressive disorders who had recently changed their treatment. Through the use of wearables<\/em>, the participants collect information on biometric data such as electrodermal activity, as well as data from the participants' mobile phones such as text messages, phone calls, use of applications, location and a biweekly survey on depression.<\/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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\u201cWe put all the data we collect from the wearable and the smartphone into our machine learning algorithm, and we try to see how well the machine learning predicts the labels given by doctors,\u201d explains Picard.<\/p>

However, another of the challenges of the machine learning application is the creation and development of a tool that gives control to users, for example, a new device, a mobile app or other methods.<\/p>

\u201cWhat might be effective is a tool that says to an individual, 'The reason you're feeling depressed might be that the data related to your sleep has changed, and the data is related to your social activity, and you haven't had time with your friends, your physical activity has been reduced. The recommendation is that you find a way to increase those things,\u201d Picard explained.<\/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

MIT<\/strong><\/p>

https:\/\/news.mit.edu\/2022\/deploying-machine-learning-improve-mental-health-rosalind-picard-0126<\/a><\/p>

HEALTH IT ANALYTICS <\/strong><\/p>

https:\/\/healthitanalytics.com\/news\/can-artificial-intelligence-boost-mental-healthcare-accessibility<\/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":"

Investigadoras del MIT y del Hospital General de Massachusetts (MGH), proponen el uso de aprendizaje autom\u00e1tico e Inteligencia Artificial (IA), para mejorar el acceso a servicios de cuidado de la salud mental. Investigadoras del MIT, plantean que la IA puede ser capaz de ayudar a que los servicios de salud mental sean m\u00e1s accesibles para los pacientes. La psic\u00f3loga e investigadora Paola Pedrelli, del MGH, explic\u00f3 que, desde su experiencia, ha encontrado diversas barreras para el acceso a la salud mental, entre ellas el cu\u00e1ndo y d\u00f3nde buscar ayuda. En este sentido, Pedrelli, en colaboraci\u00f3n con la investigadora del MIT, Rosalind Picard, han trabajado los \u00faltimos cinco a\u00f1os, en un proyecto basado en algoritmos de aprendizaje autom\u00e1tico, que busca ayudar al diagn\u00f3stico y monitoreo de s\u00edntomas de pacientes con depresi\u00f3n. \u201cEstamos tratando de construir modelos sofisticados que tengan la capacidad no solo de aprender lo que es com\u00fan entre las personas, sino tambi\u00e9n de aprender categor\u00edas de lo que est\u00e1 cambiando en la vida de un individuo\u201d, explic\u00f3 Picard. Adem\u00e1s, resalt\u00f3 que buscan brindarles a las personas la oportunidad de acceder a informaci\u00f3n personalizada basada en evidencia que realmente marque la diferencia en su salud. Las investigadoras realizaron un estudio inicial con participantes del MGH, con trastornos depresivos mayores y que hab\u00edan cambiado su tratamiento recientemente. A trav\u00e9s del uso de wearables, los participantes recolectan informaci\u00f3n sobre datos biom\u00e9tricos como actividad electrod\u00e9rmica, asimismo, se recopilaron datos de los tel\u00e9fonos m\u00f3viles de los participantes como mensajes de texto, llamadas telef\u00f3nicas, uso de aplicaciones, ubicaci\u00f3n y una encuesta quincenal sobre la depresi\u00f3n. \u201cPonemos todos los datos que recopilamos del dispositivo port\u00e1til y el tel\u00e9fono inteligente en nuestro algoritmo de aprendizaje autom\u00e1tico, y tratamos de ver qu\u00e9 tan bien el aprendizaje autom\u00e1tico predice las etiquetas dadas por los m\u00e9dicos\u201d, explica Picard. No obstante, otro de los retos de la aplicaci\u00f3n de aprendizaje autom\u00e1tico es la creaci\u00f3n y desarrollo de una herramienta que le d\u00e9 el control a los usuarios, por ejemplo, un dispositivo nuevo, una app m\u00f3vil u otros m\u00e9todos. \u201cLo que podr\u00eda ser efectivo es una herramienta que le diga a un individuo ‘La raz\u00f3n por la que te sientes deprimido podr\u00eda ser que los datos relacionados con tu sue\u00f1o hayan cambiado, y los datos se relacionen con tu actividad social, y no hayas tenido tiempo con tus amigos, tu actividad f\u00edsica se ha reducido. La recomendaci\u00f3n es que encuentre una manera de aumentar esas cosas\u201d, explic\u00f3 Picard. BIBLIOGRAF\u00cdA MIT https:\/\/news.mit.edu\/2022\/deploying-machine-learning-improve-mental-health-rosalind-picard-0126 HEALTH IT ANALYTICS https:\/\/healthitanalytics.com\/news\/can-artificial-intelligence-boost-mental-healthcare-accessibility<\/p>","protected":false},"author":1,"featured_media":23784,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[156,3393,160],"tags":[145],"class_list":["post-23782","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\/23782","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=23782"}],"version-history":[{"count":0,"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/posts\/23782\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/media\/23784"}],"wp:attachment":[{"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/media?parent=23782"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/categories?post=23782"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/tags?post=23782"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}