{"id":1803,"date":"2024-01-05T13:43:49","date_gmt":"2024-01-05T13:43:49","guid":{"rendered":"https:\/\/medicalcps.dfki.de\/?p=1803"},"modified":"2025-11-11T11:03:24","modified_gmt":"2025-11-11T11:03:24","slug":"research-grant-from-accenture","status":"publish","type":"post","link":"https:\/\/medicalcps.dfki.de\/?p=1803","title":{"rendered":"Research Grant from Accenture"},"content":{"rendered":"\n<ul class=\"wp-block-list\">\n<li><em><strong>Duration<\/strong>: January, 2024 \u2013 December, 2024<\/em><\/li>\n\n\n\n<li><em><strong>Research topics<\/strong>: Medical Text Analysis, Machine Learning &amp; Deep Learning, LLMs<\/em><\/li>\n<\/ul>\n\n\n\n<p>This research aims to investigate ChatGPT\u2019s natural language inference (NLI) capabilities in healthcare contexts, focusing on tasks like understanding clinical trial information and evidence-based health fact-checking. We will explore various Chain-of-Thought methods to improve ChatGPT\u2019s reasoning abilities and integrate dynamic context analysis techniques for better inference accuracy. Our approach involves integrating a retrieval-augmented generation framework, utilizing mechanisms such as context analysis, multi-hop reasoning, and knowledge retrieval.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"624\" src=\"https:\/\/medicalcps.dfki.de\/wp-content\/uploads\/2024\/04\/accenture_photo-1024x624.jpg\" alt=\"\" class=\"wp-image-1804\" srcset=\"https:\/\/medicalcps.dfki.de\/wp-content\/uploads\/2024\/04\/accenture_photo-1024x624.jpg 1024w, https:\/\/medicalcps.dfki.de\/wp-content\/uploads\/2024\/04\/accenture_photo-300x183.jpg 300w, https:\/\/medicalcps.dfki.de\/wp-content\/uploads\/2024\/04\/accenture_photo-768x468.jpg 768w, https:\/\/medicalcps.dfki.de\/wp-content\/uploads\/2024\/04\/accenture_photo-1536x936.jpg 1536w, https:\/\/medicalcps.dfki.de\/wp-content\/uploads\/2024\/04\/accenture_photo-2048x1248.jpg 2048w, https:\/\/medicalcps.dfki.de\/wp-content\/uploads\/2024\/04\/accenture_photo-492x300.jpg 492w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n\n\n<p><em>Siting Liang from IML presents the Autoprompt Project<\/em><\/p>\n\n\n\n<p>Sponsored by<\/p>\n\n\n\n<figure class=\"wp-block-image size-full is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"428\" height=\"118\" src=\"https:\/\/medicalcps.dfki.de\/wp-content\/uploads\/2024\/04\/accenture_logo.jpg\" alt=\"\" class=\"wp-image-1805\" style=\"width:355px;height:auto\" srcset=\"https:\/\/medicalcps.dfki.de\/wp-content\/uploads\/2024\/04\/accenture_logo.jpg 428w, https:\/\/medicalcps.dfki.de\/wp-content\/uploads\/2024\/04\/accenture_logo-300x83.jpg 300w\" sizes=\"auto, (max-width: 428px) 100vw, 428px\" \/><\/figure>\n\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>This research aims to investigate ChatGPT\u2019s natural language inference (NLI) capabilities in healthcare contexts, focusing on tasks like understanding clinical trial information and evidence-based health fact-checking. We will explore various Chain-of-Thought methods to improve ChatGPT\u2019s reasoning abilities and integrate dynamic &hellip; <a href=\"https:\/\/medicalcps.dfki.de\/?p=1803\">Continue reading <span class=\"meta-nav\">&rarr;<\/span><\/a><\/p>\n","protected":false},"author":4,"featured_media":1804,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"footnotes":""},"categories":[5],"tags":[35,34,24,32,37,18,36],"class_list":["post-1803","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news","tag-accenture","tag-chatgpt","tag-deep-learning","tag-healthcare","tag-medical-text-analysis","tag-news","tag-nli"],"_links":{"self":[{"href":"https:\/\/medicalcps.dfki.de\/index.php?rest_route=\/wp\/v2\/posts\/1803","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/medicalcps.dfki.de\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/medicalcps.dfki.de\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/medicalcps.dfki.de\/index.php?rest_route=\/wp\/v2\/users\/4"}],"replies":[{"embeddable":true,"href":"https:\/\/medicalcps.dfki.de\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=1803"}],"version-history":[{"count":2,"href":"https:\/\/medicalcps.dfki.de\/index.php?rest_route=\/wp\/v2\/posts\/1803\/revisions"}],"predecessor-version":[{"id":1807,"href":"https:\/\/medicalcps.dfki.de\/index.php?rest_route=\/wp\/v2\/posts\/1803\/revisions\/1807"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/medicalcps.dfki.de\/index.php?rest_route=\/wp\/v2\/media\/1804"}],"wp:attachment":[{"href":"https:\/\/medicalcps.dfki.de\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=1803"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/medicalcps.dfki.de\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=1803"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/medicalcps.dfki.de\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=1803"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}