- Fraunhofer researchers developed an AI system that can generate doctor’s letters about patient treatment.<\/li>
- The AI was trained on a German dataset of over 12,000 anonymous doctor’s letters.<\/li>
- Initial tests show that AI-generated letters are of similar quality to human-written ones, opening possibilities for automating clinical correspondence.<\/li><\/ul><\/div>\n\n\n\n
![\"The](\"https:\/\/www.fraunhofer.de\/en\/press\/research-news\/2023\/august-2023\/artificial-intelligence-will-soon-be-able-to-write-doctor-letters\/jcr:content\/contentPar\/sectioncomponent\/sectionParsys\/textwithinlinedimage\/imageComponent2\/image.img.jpg\/1687352275890\/iais-artificial-intelligence-will-soon-be-able-to-write-doctors-letters-pic-2.jpg\" "\\"Artificial")
<\/a>\u00a9 Fraunhofer IAIS – The patient journey at the hospital shows in which areas artificial intelligence can be used to simplify processes and support medical staff and patients. <\/figcaption><\/figure>\n\n\n\n Health data is currently one of the fastest-growing data sets. \u201cHow we process this data and what possibilities it offers for patients, care professionals, and doctors is an exciting question\u00a0\u2014 and one to which we have at least part of the answer,\u201d explains Dario Antweiler, Healthcare Analytics team leader at Fraunhofer IAIS. He has authored a white paper<\/a> with his team illuminating the current developments and opportunities for document-based processes in the medical field.<\/p>\n\n\n
<\/a><\/div><\/div>Thanks to Autoscriber, doctors pay more attention to you than to their computer<\/div>The pressure on healthcare providers is getting worse. Doctors are unable to give their patients their full attention because they spend a lot of time on administrative tasks.<\/div><\/div><\/div>\n\n\nAdditional opportunities from using Large Language Models<\/h2>\n\n\n\n
In the paper, the experts discuss Large Language Models (LLM), which have undergone drastic development in recent months, catapulting them into the public spotlight. The best-known example of an LLM currently is ChatGPT, a chatbot that creates natural-sounding texts. \u201cIn the not-too-distant future, these models will be able to work multimodally, meaning that they\u2019ll be able to process images and tabular data as well as the texts and spoken language with which they already work,\u201d explains Antweiler. This opens up new possibilities in the medical sector, which could free up staff for other tasks and improve patient treatment processes\u00a0\u2014 while considering data protection at all times.<\/p>\n\n\n\n
The healthcare sector faces numerous challenges, such as staff shortages, cost pressures and an \u201cinformation overload\u201d from the constantly increasing amounts of data. Much of the hospital data is still laboriously analyzed by hand. \u201cEvaluating, analyzing, and drawing conclusions from the data costs valuable time at various points\u00a0\u2014 a commodity lacking in the stressful day-to-day of hospitals. In the worst cases, key information goes missing, making treatments more difficult, leading to expensive reexaminations or incomplete accounting,\u201d Antweiler explains.<\/p>\n\n\n\n
Doctor\u2019s letter generator aims for market launch by the end of 2024<\/h2>\n\n\n\n
To find a solution for these problems in hospitals, the Healthcare Analytics Team at Fraunhofer IAIS is working closely with medical professionals. Together with several university hospitals, including Essen University Hospital (Universit\u00e4tsmedizin Essen), it is currently developing various possibilities for information extraction from documents. The next objective is to bring the doctor\u2019s letter generator to the market by the end of 2024, simplifying the creation of discharge letters. To do this, the AI analyzes all existing documents and creates a natural-sounding text containing easy-to-understand patient explanations. After a check, making changes or additions if required, the doctors can send the letter at the click of a button and in a fraction of the time needed to create it themselves from scratch. Another advantage is that patients, who often have to wait for this document on the day of their discharge, can leave the hospital more quickly.\u00a0\u00a0<\/p>\n\n\n
<\/a><\/div><\/div>AI halves development time medical innovations; faster and more reliable methods within reach<\/div>Research to implement innovations in healthcare takes an average of seventeen years. Especially given the speed of technological developments, that is far too long.<\/div><\/div><\/div>\n\n\nArtificial intelligence simplifies processes in hospitals<\/h2>\n\n\n\n
Other functions of Clinical NLP reduce the workload of the medical staff since the AI automatically collates critical information from a patient\u2019s medical records and makes it available to all clinical staff in a clear, structured format. Information is available in next-to-no time and can be thoroughly processed and made wholly accessible to medical staff. Dario Antweiler says: \u201cIn most hospitals, countless texts are evaluated manually every day. This is repeated in various departments and again after discharge by the family physician or specialist. Our applications make these processes fully automated, quick and precise, and\u00a0\u2014 as regards data protection\u00a0\u2014 secure, too. Healthcare systems, and especially staff and patients, would benefit from this.\u201d<\/p>\n","protected":false},"excerpt":{"rendered":"
In Germany alone, around 150 million doctor\u2019s letters are written every year. This takes precious time, which could be used elsewhere. The \u201cdoctor\u2019s letter generator\u201d, currently being developed by scientists from the Fraunhofer Institute for Intelligent Analysis and Information Systems IAIS, could provide a solution for creating the document in a fraction of the time. […]<\/p>\n","protected":false},"author":2589,"featured_media":494746,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"advgb_blocks_editor_width":"","advgb_blocks_columns_visual_guide":"","footnotes":""},"categories":[34665],"tags":[80130,6516,80132],"location":[24456],"article_type":[36684],"serie":[],"archives":[],"internal_archives":[],"reboot-archive":[],"class_list":["post-454651","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-health","tag-doctor","tag-fraunhofer","tag-fraunhofer-iais","location-germany","article_type-news"],"blocksy_meta":[],"acf":{"subtitle":"In most hospitals, countless texts are evaluated manually every day. Fraunhofer's applications make these processes fully automated, quick and precise.","text_display_homepage":false},"author_meta":{"display_name":"Team IO","author_link":"https:\/\/ioplus.nl\/archive\/author\/erikdevries\/"},"featured_img":"https:\/\/ioplus.nl\/archive\/wp-content\/uploads\/2023\/08\/Screenshot-2023-08-04-at-15.23.28.png","coauthors":[],"tax_additional":{"categories":{"linked":["Health<\/a>"],"unlinked":["Health<\/span>"]},"tags":{"linked":["doctor<\/a>","Fraunhofer<\/a>","Fraunhofer IAIS<\/a>"],"unlinked":["doctor<\/span>","Fraunhofer<\/span>","Fraunhofer IAIS<\/span>"]}},"comment_count":"0","relative_dates":{"created":"Posted 3 years ago","modified":"Updated 3 years ago"},"absolute_dates":{"created":"Posted on August 7, 2023","modified":"Updated on August 7, 2023"},"absolute_dates_time":{"created":"Posted on August 7, 2023 6:30 am","modified":"Updated on August 7, 2023 6:30 am"},"featured_img_caption":"","series_order":"","_links":{"self":[{"href":"https:\/\/ioplus.nl\/archive\/wp-json\/wp\/v2\/posts\/454651","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/ioplus.nl\/archive\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/ioplus.nl\/archive\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/ioplus.nl\/archive\/wp-json\/wp\/v2\/users\/2589"}],"replies":[{"embeddable":true,"href":"https:\/\/ioplus.nl\/archive\/wp-json\/wp\/v2\/comments?post=454651"}],"version-history":[{"count":0,"href":"https:\/\/ioplus.nl\/archive\/wp-json\/wp\/v2\/posts\/454651\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/ioplus.nl\/archive\/wp-json\/wp\/v2\/media\/494746"}],"wp:attachment":[{"href":"https:\/\/ioplus.nl\/archive\/wp-json\/wp\/v2\/media?parent=454651"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/ioplus.nl\/archive\/wp-json\/wp\/v2\/categories?post=454651"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/ioplus.nl\/archive\/wp-json\/wp\/v2\/tags?post=454651"},{"taxonomy":"location","embeddable":true,"href":"https:\/\/ioplus.nl\/archive\/wp-json\/wp\/v2\/location?post=454651"},{"taxonomy":"article_type","embeddable":true,"href":"https:\/\/ioplus.nl\/archive\/wp-json\/wp\/v2\/article_type?post=454651"},{"taxonomy":"serie","embeddable":true,"href":"https:\/\/ioplus.nl\/archive\/wp-json\/wp\/v2\/serie?post=454651"},{"taxonomy":"archives","embeddable":true,"href":"https:\/\/ioplus.nl\/archive\/wp-json\/wp\/v2\/archives?post=454651"},{"taxonomy":"internal_archives","embeddable":true,"href":"https:\/\/ioplus.nl\/archive\/wp-json\/wp\/v2\/internal_archives?post=454651"},{"taxonomy":"reboot-archive","embeddable":true,"href":"https:\/\/ioplus.nl\/archive\/wp-json\/wp\/v2\/reboot-archive?post=454651"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
![\"The](\"https:\/\/www.fraunhofer.de\/en\/press\/research-news\/2023\/august-2023\/artificial-intelligence-will-soon-be-able-to-write-doctor-letters\/jcr:content\/contentPar\/sectioncomponent\/sectionParsys\/textwithinlinedimage\/imageComponent2\/image.img.4col.large.jpg\/1687352275890\/iais-artificial-intelligence-will-soon-be-able-to-write-doctors-letters-pic-2.jpg\" "\\"Artificial")
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