{"id":833,"date":"2026-07-14T15:14:03","date_gmt":"2026-07-14T14:14:03","guid":{"rendered":"https:\/\/schools.stem.open.ac.uk\/knowledge-media-institute\/?page_id=833"},"modified":"2026-07-14T15:14:03","modified_gmt":"2026-07-14T14:14:03","slug":"deep-learning-for-information-extraction-from-cancer-pathology-reports","status":"publish","type":"page","link":"https:\/\/schools.stem.open.ac.uk\/knowledge-media-institute\/deep-learning-for-information-extraction-from-cancer-pathology-reports\/","title":{"rendered":"Deep Learning for Information Extraction from Cancer Pathology Reports"},"content":{"rendered":"\n
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Shang Gao – University of Tennessee
This event took place on Tuesday 19 March 2019 at 11:30<\/small><\/p>\n<\/div>\n\n\n\n


Medical text can present unique challenges for natural language processing (NLP) including documents that are several pages long, linguistic dependencies over different report sections, and only a tiny fraction of the report text being relevant to a specific information retrieval task. Many out-of-the-box deep learning architectures adapted from general NLP tasks are unable to efficiently tackle these challenges. This talk will cover the foundations of deep learning for NLP and then discuss how these architectures can be adapted for long medical texts. This talk will focus on the application of cancer pathology reports, but the techniques are applicable towards general biomedical and scientific NLP tasks in which specific information must be extracted from long documents.<\/p>\n\n\n\n

Watch the webcast replay >><\/a><\/p>\n\n\n\n

View all past events<\/a><\/p>\n\n\n\n

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\"Maven<\/figure>\n\n\n\n
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Maven of the Month<\/a><\/h3>\n\n\n\n

We are also inviting top experts in AI and Knowledge Technologies to discuss major socio-technological topics with an audience that comprises both members of the Knowledge Media Institute, as well as the wider staff at The Open University. Differently from our seminar series, these events follow a Q&A format.<\/p>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

Shang Gao – University of TennesseeThis event took place on Tuesday 19 March 2019 at 11:30 Medical text can present unique challenges for natural language processing (NLP) including documents that are several pages long, linguistic dependencies over different report sections, and only a tiny fraction of the report text being relevant to a specific information […]<\/p>\n","protected":false},"author":13,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"unity_related_person":[],"unity_sdg":[],"unity_research_theme":[],"unity_strategic_priority":[],"unity_enabler":[],"unity_general_category":[],"unity_stem_unit":[],"unity_related_project":[],"unity_related_archived_project":[],"unity_related_event":[],"class_list":["post-833","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/schools.stem.open.ac.uk\/knowledge-media-institute\/wp-json\/wp\/v2\/pages\/833","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/schools.stem.open.ac.uk\/knowledge-media-institute\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/schools.stem.open.ac.uk\/knowledge-media-institute\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/schools.stem.open.ac.uk\/knowledge-media-institute\/wp-json\/wp\/v2\/users\/13"}],"replies":[{"embeddable":true,"href":"https:\/\/schools.stem.open.ac.uk\/knowledge-media-institute\/wp-json\/wp\/v2\/comments?post=833"}],"version-history":[{"count":1,"href":"https:\/\/schools.stem.open.ac.uk\/knowledge-media-institute\/wp-json\/wp\/v2\/pages\/833\/revisions"}],"predecessor-version":[{"id":834,"href":"https:\/\/schools.stem.open.ac.uk\/knowledge-media-institute\/wp-json\/wp\/v2\/pages\/833\/revisions\/834"}],"wp:attachment":[{"href":"https:\/\/schools.stem.open.ac.uk\/knowledge-media-institute\/wp-json\/wp\/v2\/media?parent=833"}],"wp:term":[{"taxonomy":"unity_related_person","embeddable":true,"href":"https:\/\/schools.stem.open.ac.uk\/knowledge-media-institute\/wp-json\/wp\/v2\/unity_related_person?post=833"},{"taxonomy":"unity_sdg","embeddable":true,"href":"https:\/\/schools.stem.open.ac.uk\/knowledge-media-institute\/wp-json\/wp\/v2\/unity_sdg?post=833"},{"taxonomy":"unity_research_theme","embeddable":true,"href":"https:\/\/schools.stem.open.ac.uk\/knowledge-media-institute\/wp-json\/wp\/v2\/unity_research_theme?post=833"},{"taxonomy":"unity_strategic_priority","embeddable":true,"href":"https:\/\/schools.stem.open.ac.uk\/knowledge-media-institute\/wp-json\/wp\/v2\/unity_strategic_priority?post=833"},{"taxonomy":"unity_enabler","embeddable":true,"href":"https:\/\/schools.stem.open.ac.uk\/knowledge-media-institute\/wp-json\/wp\/v2\/unity_enabler?post=833"},{"taxonomy":"unity_general_category","embeddable":true,"href":"https:\/\/schools.stem.open.ac.uk\/knowledge-media-institute\/wp-json\/wp\/v2\/unity_general_category?post=833"},{"taxonomy":"unity_stem_unit","embeddable":true,"href":"https:\/\/schools.stem.open.ac.uk\/knowledge-media-institute\/wp-json\/wp\/v2\/unity_stem_unit?post=833"},{"taxonomy":"unity_related_project","embeddable":true,"href":"https:\/\/schools.stem.open.ac.uk\/knowledge-media-institute\/wp-json\/wp\/v2\/unity_related_project?post=833"},{"taxonomy":"unity_related_archived_project","embeddable":true,"href":"https:\/\/schools.stem.open.ac.uk\/knowledge-media-institute\/wp-json\/wp\/v2\/unity_related_archived_project?post=833"},{"taxonomy":"unity_related_event","embeddable":true,"href":"https:\/\/schools.stem.open.ac.uk\/knowledge-media-institute\/wp-json\/wp\/v2\/unity_related_event?post=833"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}