{"id":21493,"date":"2024-05-09T17:14:00","date_gmt":"2024-05-09T15:14:00","guid":{"rendered":"https:\/\/mediaire.ai\/?p=21493"},"modified":"2025-09-03T09:04:59","modified_gmt":"2025-09-03T07:04:59","slug":"changes-in-mri-workflow-of-multiple-sclerosis-after-introduction-of-an-ai-software-a-qualitative-study","status":"publish","type":"post","link":"https:\/\/mediaire.ai\/en\/changes-in-mri-workflow-of-multiple-sclerosis-after-introduction-of-an-ai-software-a-qualitative-study\/","title":{"rendered":"Changes in MRI Workflow of Multiple Sclerosis after Introduction of an AI-Software: A Qualitative Study"},"content":{"rendered":"
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Healthcare 2024<\/em>, 12<\/em>, 978. https:\/\/doi.org\/10.3390\/healthcare12100978<\/p>\n

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Rathmann, E., Hemkemeier, P., Raths, S., Grothe, M., Mankertz, F., Hosten, N., Flessa, S.<\/p>\n

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Abstract<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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The purpose of this study was to explore the effects of the integration of machine learning into daily radiological diagnostics, using the example of the machine learning software mdbrain\u00ae<\/sup> (Mediaire GmbH, Germany) in the diagnostic MRI workflow of patients with multiple sclerosis at the University Medicine Greifswald.<\/p>\n

The data were assessed through expert interviews, a comparison of analysis times with and without the machine learning software, as well as a process analysis of MRI workflows.<\/p>\n

Our results indicate a reduction in the screen-reading workload, improved decision-making regarding contrast administration, an optimized workflow, reduced examination times, and facilitated report communication with colleagues and patients. Our results call for a broader and quantitative analysis.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tRead Full Publication<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\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<\/div>","protected":false},"excerpt":{"rendered":"

The purpose of this study was to explore the effects of the integration of machine learning into daily radiological diagnostics, using the example of the machine learning software mdbrain\u00ae (Mediaire GmbH, Germany) in the diagnostic MRI workflow of patients with multiple sclerosis at the University Medicine Greifswald.<\/p>","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[14],"tags":[],"class_list":["post-21493","post","type-post","status-publish","format-standard","hentry","category-publications"],"acf":[],"_links":{"self":[{"href":"https:\/\/mediaire.ai\/en\/wp-json\/wp\/v2\/posts\/21493","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/mediaire.ai\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/mediaire.ai\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/mediaire.ai\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/mediaire.ai\/en\/wp-json\/wp\/v2\/comments?post=21493"}],"version-history":[{"count":6,"href":"https:\/\/mediaire.ai\/en\/wp-json\/wp\/v2\/posts\/21493\/revisions"}],"predecessor-version":[{"id":21625,"href":"https:\/\/mediaire.ai\/en\/wp-json\/wp\/v2\/posts\/21493\/revisions\/21625"}],"wp:attachment":[{"href":"https:\/\/mediaire.ai\/en\/wp-json\/wp\/v2\/media?parent=21493"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/mediaire.ai\/en\/wp-json\/wp\/v2\/categories?post=21493"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/mediaire.ai\/en\/wp-json\/wp\/v2\/tags?post=21493"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}