{"id":3130,"date":"2023-11-02T08:29:40","date_gmt":"2023-11-02T08:29:40","guid":{"rendered":"https:\/\/caimed.de\/?page_id=3130"},"modified":"2026-01-27T07:48:53","modified_gmt":"2026-01-27T06:48:53","slug":"ki-semantik","status":"publish","type":"page","link":"https:\/\/caimed.de\/en\/forschung\/ki-semantik\/","title":{"rendered":"AI & Semantics"},"content":{"rendered":"
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AI & Semantics<\/h1>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n
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Die Analyse umfangreicher medizinischer Daten f\u00fcr klinische Entscheidungen erfordert nicht nur das Erkennen statistischer Beziehungen, sondern auch das Verst\u00e4ndnis kausaler Zusammenh\u00e4nge in biologischen Prozessen. Die Nutzung von kausalen\n und datengetriebenen Modellen macht diese robuster und verst\u00e4ndlicher. Methoden des maschinellen Lernens schlagen eine Br\u00fccke zwischen klinischen Informationen, Bildgebung, Laborwerten und elektronischen Gesundheitsakten f\u00fcr ein\n ganzheitliches Bild der PatientInnen. Vielversprechend ist die Entwicklung von Evidenzsyntheseverfahren, die heterogene Datenquellen integrieren und auf kontrafaktischen Methoden, Meta-Analyse und k\u00fcnstlichen neuronalen Netzen basieren.\n Die Bildung von Nachwuchsgruppen zu den Themen AI and Causality, AI and Bioinformatics, KI-Systeme in Multi-Omics Daten und Statistische Evidenz in KI-Systemen soll das Potenzial im Bereich „KI und Semantik“ erschlie\u00dfen.<\/p>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n

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\n \n \n AI & Semantics<\/span>\n
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Trustworthy AI & Causality<\/h6>\n <\/a>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n
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AI & Bioinformatics<\/h6>\n <\/a>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n
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Multi-Omics Data<\/h6>\n <\/a>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n
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Statistical Evidence<\/h6>\n <\/a>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n<\/div>","protected":false},"excerpt":{"rendered":"

KI & Semantik Die Analyse umfangreicher medizinischer Daten f\u00fcr klinische Entscheidungen erfordert nicht nur das Erkennen statistischer Beziehungen, sondern auch das Verst\u00e4ndnis kausaler Zusammenh\u00e4nge in biologischen Prozessen. Die Nutzung von kausalen und datengetriebenen Modellen macht diese robuster und verst\u00e4ndlicher. Methoden des maschinellen Lernens schlagen eine Br\u00fccke zwischen klinischen Informationen, Bildgebung, Laborwerten und elektronischen Gesundheitsakten f\u00fcr […]<\/p>","protected":false},"author":4,"featured_media":0,"parent":2907,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"page-templates\/full-width-page.php","meta":{"footnotes":""},"class_list":["post-3130","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/caimed.de\/en\/wp-json\/wp\/v2\/pages\/3130","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/caimed.de\/en\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/caimed.de\/en\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/caimed.de\/en\/wp-json\/wp\/v2\/users\/4"}],"replies":[{"embeddable":true,"href":"https:\/\/caimed.de\/en\/wp-json\/wp\/v2\/comments?post=3130"}],"version-history":[{"count":7,"href":"https:\/\/caimed.de\/en\/wp-json\/wp\/v2\/pages\/3130\/revisions"}],"predecessor-version":[{"id":14348,"href":"https:\/\/caimed.de\/en\/wp-json\/wp\/v2\/pages\/3130\/revisions\/14348"}],"up":[{"embeddable":true,"href":"https:\/\/caimed.de\/en\/wp-json\/wp\/v2\/pages\/2907"}],"wp:attachment":[{"href":"https:\/\/caimed.de\/en\/wp-json\/wp\/v2\/media?parent=3130"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}