{"id":2501,"date":"2022-10-04T08:30:57","date_gmt":"2022-10-04T08:30:57","guid":{"rendered":"https:\/\/medgift.hevs.ch\/wordpress\/?p=2501"},"modified":"2022-10-04T08:30:57","modified_gmt":"2022-10-04T08:30:57","slug":"new-article-presenting-sket-the-semantic-knowledge-extractor-tool","status":"publish","type":"post","link":"https:\/\/medgift.hevs.ch\/wordpress\/new-article-presenting-sket-the-semantic-knowledge-extractor-tool\/","title":{"rendered":"New article  presenting SKET &#8211; The Semantic Knowledge Extractor Tool"},"content":{"rendered":"\n<p>Our article entitled <a href=\"https:\/\/www.sciencedirect.com\/science\/article\/pii\/S2153353922007337?SIS_ID=&amp;dgcid=STMJ_AUTH_SERV_PUBLISHED&amp;CMX_ID=\">&#8220;Empowering Digital Pathology Applications through Explainable Knowledge Extraction Tools<\/a>&#8221; has been published in Journal of Pathology Informatics.<\/p>\n\n\n\n<p>The Semantic Knowledge Extractor Tool (SKET) is an unsupervised hybrid system that combines rule-based techniques with pre-trained machine learning models to extract key pathological concepts from diagnostic reports. SKET is a viable solution to reduce pathologists\u2019 workload and can be used as a first, cheap solution to bootstrap supervised models in absence of manual annotations.<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"729\" height=\"342\" src=\"https:\/\/medgift.hevs.ch\/wordpress\/wp-content\/uploads\/2022\/10\/FeJB4DpWYAABm_V.jpeg\" alt=\"\" class=\"wp-image-2502\" srcset=\"https:\/\/medgift.hevs.ch\/wordpress\/wp-content\/uploads\/2022\/10\/FeJB4DpWYAABm_V.jpeg 729w, https:\/\/medgift.hevs.ch\/wordpress\/wp-content\/uploads\/2022\/10\/FeJB4DpWYAABm_V-300x141.jpeg 300w\" sizes=\"auto, (max-width: 729px) 100vw, 729px\" \/><figcaption>SKET architecture.<\/figcaption><\/figure>\n\n\n\n<p>The SKET eXplained (SKET X) is a web-based system that supports pathologists and domain experts in the visual understanding of SKET predictions. SKET X can refine parameters and rules over time, thus improving the system effectiveness and increasing user\u2019s trust and confidence<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"622\" height=\"331\" src=\"https:\/\/medgift.hevs.ch\/wordpress\/wp-content\/uploads\/2022\/10\/FeJC6oTXgAIiSML.jpeg\" alt=\"\" class=\"wp-image-2503\" srcset=\"https:\/\/medgift.hevs.ch\/wordpress\/wp-content\/uploads\/2022\/10\/FeJC6oTXgAIiSML.jpeg 622w, https:\/\/medgift.hevs.ch\/wordpress\/wp-content\/uploads\/2022\/10\/FeJC6oTXgAIiSML-300x160.jpeg 300w\" sizes=\"auto, (max-width: 622px) 100vw, 622px\" \/><figcaption>SKET X dashboard providing information about the executed SKET pipelines<\/figcaption><\/figure>\n","protected":false},"excerpt":{"rendered":"<p>Our article entitled &#8220;Empowering Digital Pathology Applications through Explainable Knowledge Extraction Tools&#8221; has been published in Journal of Pathology Informatics. The Semantic Knowledge Extractor Tool (SKET) is an unsupervised hybrid system that combines rule-based techniques with pre-trained machine learning models to extract key pathological concepts from diagnostic reports. SKET is a viable solution to reduce &hellip; <\/p>\n<p class=\"link-more\"><a href=\"https:\/\/medgift.hevs.ch\/wordpress\/new-article-presenting-sket-the-semantic-knowledge-extractor-tool\/\" class=\"more-link\">Continue reading<span class=\"screen-reader-text\"> &#8220;New article  presenting SKET &#8211; The Semantic Knowledge Extractor Tool&#8221;<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[1],"tags":[],"class_list":["post-2501","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"jetpack_featured_media_url":"","jetpack_shortlink":"https:\/\/wp.me\/p8AP2d-El","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/medgift.hevs.ch\/wordpress\/wp-json\/wp\/v2\/posts\/2501","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/medgift.hevs.ch\/wordpress\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/medgift.hevs.ch\/wordpress\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/medgift.hevs.ch\/wordpress\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/medgift.hevs.ch\/wordpress\/wp-json\/wp\/v2\/comments?post=2501"}],"version-history":[{"count":1,"href":"https:\/\/medgift.hevs.ch\/wordpress\/wp-json\/wp\/v2\/posts\/2501\/revisions"}],"predecessor-version":[{"id":2504,"href":"https:\/\/medgift.hevs.ch\/wordpress\/wp-json\/wp\/v2\/posts\/2501\/revisions\/2504"}],"wp:attachment":[{"href":"https:\/\/medgift.hevs.ch\/wordpress\/wp-json\/wp\/v2\/media?parent=2501"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/medgift.hevs.ch\/wordpress\/wp-json\/wp\/v2\/categories?post=2501"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/medgift.hevs.ch\/wordpress\/wp-json\/wp\/v2\/tags?post=2501"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}