{"id":13956,"date":"2021-04-20T13:46:22","date_gmt":"2021-04-20T18:46:22","guid":{"rendered":"https:\/\/saluddigital.com\/?p=13956"},"modified":"2025-10-21T12:48:54","modified_gmt":"2025-10-21T18:48:54","slug":"publican-estudio-sobre-la-evaluacion-de-la-precision-del-aprendizaje-profundo-en-analisis-de-imagenes-medicas","status":"publish","type":"post","link":"https:\/\/saluddigital.com\/en\/big-data\/publican-estudio-sobre-la-evaluacion-de-la-precision-del-aprendizaje-profundo-en-analisis-de-imagenes-medicas\/","title":{"rendered":"Study on accuracy assessment of deep learning in medical image analysis was published"},"content":{"rendered":"
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The article \"Diagnostic accuracy of deep learning in medical imaging: a systematic review and meta-analysis\" published in Nature, presents an assessment of the diagnostic accuracy of deep learning through the review of more than 11,921studies related to the topic.<\/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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Deep learning (DL), one of the subfields of Artificial Intelligence, is capable of changing medical diagnoses as we know them. However, despite advances in science, its diagnostic accuracy is still uncertain. The objective of the aforementioned study was to \"evaluate the diagnostic accuracy of DL algorithms to identify pathology in medical imaging.\"<\/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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\"Successful integration of DL technology into routine clinical practice relies upon achieving diagnostic accuracy that is non-inferior to healthcare professionals. In addition, it must provide other benefits, such as speed, efficiency, cost, bolstering accessibility and the maintenance of ethical conduct,\" the authors explain about the use of deep learning in medical practice.<\/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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By searching for articles related to deep learning in the Medline and EMBASE databases, they identified more than 11,000 studies, of which 503 were finally systematically reviewed.<\/p>

\"Eighty-two studies in ophthalmology, 82 in breast disease and 115 in respiratory disease were included for meta-analysis. Two hundred twenty-four studies in other specialities were included for qualitative review. Peer-reviewed studies that reported on the diagnostic accuracy of DL algorithms to identify pathology using medical imaging were included,\" the authors explain.<\/p>

Across specialty areas the results show different outcomes, \"Terminology and outcome measures was noted. This can lead to an overestimation of the diagnostic accuracy of DL algorithms on medical imaging,\" they acknowledge.<\/p>

Finally, the authors comment that the rapid development of AI- or DL-based technologies has great potential in healthcare, especially in radiology. \"This systematic review and meta-analysis appraised the quality of the literature and provided pooled diagnostic accuracy for DL techniques in three medical specialities,\" they conclude.<\/p>

Read the full text at the following link: https:\/\/www.nature.com\/articles\/s41746-021-00438-z<\/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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NATURE<\/strong><\/p>

https:\/\/www.nature.com\/articles\/s41746-021-00438-z<\/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":"

El art\u00edculo “Precisi\u00f3n diagn\u00f3stica del aprendizaje profundo en im\u00e1genes m\u00e9dicas: una revisi\u00f3n sistem\u00e1tica y un metaan\u00e1lisis” publicado en Nature, presenta una evaluaci\u00f3n de la precisi\u00f3n diagn\u00f3stica del aprendizaje profundo a trav\u00e9s de la revisi\u00f3n de m\u00e1s de 11,921 estudios relacionados al tema. El aprendizaje profundo o Deep learning (DL), uno de los subcampos de la Inteligencia Artificial, es capaz de cambiar los diagn\u00f3sticos m\u00e9dicos como los conocemos. Sin embargo, a pesar de los avances de la ciencia, su precisi\u00f3n diagn\u00f3stica a\u00fan es incierta. El objetivo del estudio antes mencionado tuvo como objetivo \u201cevaluar la precisi\u00f3n diagn\u00f3stica de los algoritmos DL para identificar patolog\u00edas en im\u00e1genes m\u00e9dicas\u201d. \u201cLa integraci\u00f3n exitosa de la tecnolog\u00eda DL en la pr\u00e1ctica cl\u00ednica de rutina se basa en lograr una precisi\u00f3n diagn\u00f3stica que no sea inferior a la de los profesionales de la salud. Adem\u00e1s, debe aportar otros beneficios, como rapidez, eficiencia, coste, potenciaci\u00f3n de la accesibilidad y mantenimiento de la conducta \u00e9tica\u201d, explican los autores sobre el uso de aprendizaje profundo en el ejercicio m\u00e9dico. A trav\u00e9s de la b\u00fasqueda de art\u00edculos relacionados a aprendizaje profundo, en las bases de datos Medline y EMBASE, identificaron m\u00e1s de 11 mil estudios de los cuales 503 fueron finalmente revisados sistem\u00e1ticamente. \u201cSe incluyeron para el metaan\u00e1lisis 82 estudios en oftalmolog\u00eda, 82 en enfermedad mamaria y 115 en enfermedad respiratoria. Se incluyeron doscientos veinticuatro estudios en otras especialidades para revisi\u00f3n cualitativa. Se incluyeron estudios revisados \u200b\u200bpor pares que informaron sobre la precisi\u00f3n diagn\u00f3stica de los algoritmos de DL para identificar patolog\u00edas mediante im\u00e1genes m\u00e9dicas\u201d, explican los autores. En las distintas \u00e1reas de especialidad los resultados muestran diferentes resultados, \u201cuna amplia variaci\u00f3n en la metodolog\u00eda, la interpretabilidad de los datos, la terminolog\u00eda y las medidas de resultado podr\u00edan explicarse por la falta de consenso sobre c\u00f3mo realizar e informar los estudios de DL”, reconocen. Finalmente, los autores comentan que la rapidez del desarrollo de tecnolog\u00edas basadas en IA o DL, tienen un gran potencial en atenci\u00f3n m\u00e9dica, sobre todo en radiolog\u00eda. “esta revisi\u00f3n sistem\u00e1tica y metaan\u00e1lisis evalu\u00f3 la calidad de la literatura y brind\u00f3 precisi\u00f3n diagn\u00f3stica combinada para las t\u00e9cnicas de LD en tres especialidades m\u00e9dicas”, finalizan. Lee el texto completo en el siguiente enlace: https:\/\/www.nature.com\/articles\/s41746-021-00438-z BIBLIOGRAF\u00cdA NATURE https:\/\/www.nature.com\/articles\/s41746-021-00438-z<\/p>","protected":false},"author":1,"featured_media":13957,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[3399,156,3393,1418],"tags":[145],"class_list":["post-13956","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai-analitica","category-big-data","category-inteligencia-artificial-y-ciencia","category-resena-de-publicaciones-cientificas","tag-noticias"],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/posts\/13956","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=13956"}],"version-history":[{"count":0,"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/posts\/13956\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/media\/13957"}],"wp:attachment":[{"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/media?parent=13956"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/categories?post=13956"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/tags?post=13956"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}