{"id":27535,"date":"2025-12-19T10:24:36","date_gmt":"2025-12-19T09:24:36","guid":{"rendered":"https:\/\/sano.science\/?p=27535"},"modified":"2025-12-19T10:26:11","modified_gmt":"2025-12-19T09:26:11","slug":"ai-driven-clustering-of-allergy-profiles-presented-at-ieee-icprs-25-in-chile","status":"publish","type":"post","link":"https:\/\/sano.science\/ai-driven-clustering-of-allergy-profiles-presented-at-ieee-icprs-25-in-chile\/","title":{"rendered":"AI\u2011Driven Clustering of Allergy Profiles Presented at IEEE ICPRS\u201125 in Chile"},"content":{"rendered":"\n<p class=\" eplus-wrapper\"><a href=\"https:\/\/sano.science\/people\/maja-szczypka\/\">Maja Szczypka<\/a>,\u00a0member of the Computational Intelligence Team at Sano Centre for Computational Medicine, represented Sano at the IEEE 15th International Conference on Pattern Recognition Systems (ICPRS-25), held in Vi\u00f1a del Mar, Chile. The event was organised by the University Adolfo Ib\u00e1\u00f1ez and the Chilean Association for Pattern Recognition (ACHiRP), endorsed by the IAPR and the IEEE Chile Section, and brought together researchers from around the world to discuss advances and challenges in pattern recognition systems.\u00a0<\/p>\n\n\n\n<div style=\"height:30px\" aria-hidden=\"true\" class=\"wp-block-spacer eplus-wrapper\"><\/div>\n\n\n\n<h2 class=\"wp-block-heading eplus-wrapper\" id=\"h-presentation-on-clustering-nbsp-allergy-nbsp-diagnoses-nbsp\">Presentation on Clustering&nbsp;Allergy&nbsp;Diagnoses&nbsp;<\/h2>\n\n\n\n<p class=\" eplus-wrapper\">During the conference, Maja delivered a presentation entitled \u201c<strong>Patterns Beyond Labels: Clustering Allergy Diagnoses in Overlapping Clinical Profiles<\/strong>.\u201d Her talk showcased a step-by-step process for identifying groups of patients with similar clinical profiles using real-world hospital data provided by the Allergy Department of the Voivodeship Hospital for Children in Ameryka, Poland.<\/p>\n\n\n\n<p class=\" eplus-wrapper\">The presentation highlighted the complexities of working with clinical datasets that were not originally intended for machine learning applications and the challenges that arise when standard ML methods require strict assumptions. Maja also emphasized the importance of continuous collaboration with domain experts to correctly interpret results and fully understand the underlying data limitations.&nbsp;<\/p>\n\n\n\n<div style=\"height:30px\" aria-hidden=\"true\" class=\"wp-block-spacer eplus-wrapper\"><\/div>\n\n\n\n<h2 class=\"wp-block-heading eplus-wrapper\" id=\"h-strengthening-nbsp-research-nbsp-collaboration-nbsp\">Strengthening&nbsp;Research&nbsp;Collaboration&nbsp;<\/h2>\n\n\n\n<p class=\" eplus-wrapper\">This participation strengthened Sano\u2019s engagement in the international research community working at the intersection of machine learning and healthcare. It also showcased how computational approaches can support clinical decision-making and deepen understanding of complex medical conditions.<\/p>\n","protected":false},"excerpt":"Maja Szczypka,\u00a0member of the Computational Intelligence Team at Sano Centre for Computational Medicine, represented Sano at the IEEE 15th International Conference on Pattern Recognition Systems (ICPRS-25), held in Vi\u00f1a del Mar, Chile. The event was organised by the University Adolfo Ib\u00e1\u00f1ez and the Chilean Association for Pattern Recognition (ACHiRP), endorsed by the IAPR and the [&hellip;]","author":8,"featured_media":27539,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"editor_plus_post_options":"{}","editor_plus_copied_stylings":"{}","footnotes":""},"categories":[1],"tags":[],"class_list":["post-27535","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized"],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v27.3 (Yoast SEO v27.3) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>AI\u2011Driven Clustering of Allergy Profiles Presented at IEEE ICPRS<\/title>\n<meta name=\"description\" content=\"During the IEEE 15th ICPRS\u201125 in Chile, Sano showcased how machine\u2011learning\u2011based clustering of 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class=\" eplus-wrapper\"><a href=\"https:\/\/sano.science\/people\/maja-szczypka\/\">Maja Szczypka<\/a>,\u00a0member of the Computational Intelligence Team at Sano Centre for Computational Medicine, represented Sano at the IEEE 15th International Conference on Pattern Recognition Systems (ICPRS-25), held in Vi\u00f1a del Mar, Chile. The event was organised by the University Adolfo Ib\u00e1\u00f1ez and the Chilean Association for Pattern Recognition (ACHiRP), endorsed by the IAPR and the IEEE Chile Section, and brought together researchers from around the world to discuss advances and challenges in pattern recognition systems.\u00a0<\/p>\n","innerContent":["\n<p class=\" eplus-wrapper\"><a href=\"https:\/\/sano.science\/people\/maja-szczypka\/\">Maja Szczypka<\/a>,\u00a0member of the Computational Intelligence Team at Sano Centre for Computational Medicine, represented Sano at the IEEE 15th International Conference on Pattern Recognition Systems (ICPRS-25), held in Vi\u00f1a del Mar, Chile. The event was organised by the University Adolfo Ib\u00e1\u00f1ez and the Chilean Association for Pattern Recognition (ACHiRP), endorsed by the IAPR and the IEEE Chile Section, and brought together researchers from around the world to discuss advances and challenges in pattern recognition systems.\u00a0<\/p>\n"]},{"blockName":"core\/spacer","attrs":{"height":"30px","epAnimationGeneratedClass":"edplus_anim-s87B2V","epGeneratedClass":"eplus-wrapper"},"innerBlocks":[],"innerHTML":"\n<div style=\"height:30px\" aria-hidden=\"true\" class=\"wp-block-spacer eplus-wrapper\"><\/div>\n","innerContent":["\n<div style=\"height:30px\" aria-hidden=\"true\" class=\"wp-block-spacer eplus-wrapper\"><\/div>\n"]},{"blockName":"core\/heading","attrs":{"epAnimationGeneratedClass":"edplus_anim-IgdOFH","epGeneratedClass":"eplus-wrapper"},"innerBlocks":[],"innerHTML":"\n<h2 class=\"wp-block-heading eplus-wrapper\" id=\"h-presentation-on-clustering-nbsp-allergy-nbsp-diagnoses-nbsp\">Presentation on Clustering&nbsp;Allergy&nbsp;Diagnoses&nbsp;<\/h2>\n","innerContent":["\n<h2 class=\"wp-block-heading eplus-wrapper\" id=\"h-presentation-on-clustering-nbsp-allergy-nbsp-diagnoses-nbsp\">Presentation on Clustering&nbsp;Allergy&nbsp;Diagnoses&nbsp;<\/h2>\n"]},{"blockName":"core\/paragraph","attrs":{"epAnimationGeneratedClass":"edplus_anim-7DxUCd","epGeneratedClass":"eplus-wrapper"},"innerBlocks":[],"innerHTML":"\n<p class=\" eplus-wrapper\">During the conference, Maja delivered a presentation entitled \u201c<strong>Patterns Beyond Labels: Clustering Allergy Diagnoses in Overlapping Clinical Profiles<\/strong>.\u201d Her talk showcased a step-by-step process for identifying groups of patients with similar clinical profiles using real-world hospital data provided by the Allergy Department of the Voivodeship Hospital for Children in Ameryka, Poland.<\/p>\n","innerContent":["\n<p class=\" eplus-wrapper\">During the conference, Maja delivered a presentation entitled \u201c<strong>Patterns Beyond Labels: Clustering Allergy Diagnoses in Overlapping Clinical Profiles<\/strong>.\u201d Her talk showcased a step-by-step process for identifying groups of patients with similar clinical profiles using real-world hospital data provided by the Allergy Department of the Voivodeship Hospital for Children in Ameryka, Poland.<\/p>\n"]},{"blockName":"core\/paragraph","attrs":{"epAnimationGeneratedClass":"edplus_anim-x5ZTVF","epGeneratedClass":"eplus-wrapper"},"innerBlocks":[],"innerHTML":"\n<p class=\" eplus-wrapper\">The presentation highlighted the complexities of working with clinical datasets that were not originally intended for machine learning applications and the challenges that arise when standard ML methods require strict assumptions. Maja also emphasized the importance of continuous collaboration with domain experts to correctly interpret results and fully understand the underlying data limitations.&nbsp;<\/p>\n","innerContent":["\n<p class=\" eplus-wrapper\">The presentation highlighted the complexities of working with clinical datasets that were not originally intended for machine learning applications and the challenges that arise when standard ML methods require strict assumptions. Maja also emphasized the importance of continuous collaboration with domain experts to correctly interpret results and fully understand the underlying data limitations.&nbsp;<\/p>\n"]},{"blockName":"core\/spacer","attrs":{"height":"30px","epAnimationGeneratedClass":"edplus_anim-s87B2V","epGeneratedClass":"eplus-wrapper"},"innerBlocks":[],"innerHTML":"\n<div style=\"height:30px\" aria-hidden=\"true\" class=\"wp-block-spacer eplus-wrapper\"><\/div>\n","innerContent":["\n<div style=\"height:30px\" aria-hidden=\"true\" class=\"wp-block-spacer eplus-wrapper\"><\/div>\n"]},{"blockName":"core\/heading","attrs":{"epAnimationGeneratedClass":"edplus_anim-NyI22T","epGeneratedClass":"eplus-wrapper"},"innerBlocks":[],"innerHTML":"\n<h2 class=\"wp-block-heading eplus-wrapper\" id=\"h-strengthening-nbsp-research-nbsp-collaboration-nbsp\">Strengthening&nbsp;Research&nbsp;Collaboration&nbsp;<\/h2>\n","innerContent":["\n<h2 class=\"wp-block-heading eplus-wrapper\" id=\"h-strengthening-nbsp-research-nbsp-collaboration-nbsp\">Strengthening&nbsp;Research&nbsp;Collaboration&nbsp;<\/h2>\n"]},{"blockName":"core\/paragraph","attrs":{"epAnimationGeneratedClass":"edplus_anim-FcMtDS","epGeneratedClass":"eplus-wrapper"},"innerBlocks":[],"innerHTML":"\n<p class=\" eplus-wrapper\">This participation strengthened Sano\u2019s engagement in the international research community working at the intersection of machine learning and healthcare. It also showcased how computational approaches can support clinical decision-making and deepen understanding of complex medical conditions.<\/p>\n","innerContent":["\n<p class=\" eplus-wrapper\">This participation strengthened Sano\u2019s engagement in the international research community working at the intersection of machine learning and healthcare. It also showcased how computational approaches can support clinical decision-making and deepen understanding of complex medical conditions.<\/p>\n"]}],"meta_data":{"has_thumbnail_pattern":false,"share_on_social_media":{"has_social_media":false}},"featured_image":{"url":"https:\/\/sano.science\/wp-content\/uploads\/2025\/12\/IEEE-ICPRS\u201125-Maja-Szczypka-917x1024.jpg"},"main_category":{"name":"Uncategorized"},"prev_page":{"slug":"przemyslaw-korzeniowski-and-sanos-innovations-at-the-26th-nfic-workshop"},"next_page":{"slug":"young-science-explorers"},"_links":{"self":[{"href":"https:\/\/sano.science\/index.php\/wp-json\/wp\/v2\/posts\/27535","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/sano.science\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/sano.science\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/sano.science\/index.php\/wp-json\/wp\/v2\/users\/8"}],"replies":[{"embeddable":true,"href":"https:\/\/sano.science\/index.php\/wp-json\/wp\/v2\/comments?post=27535"}],"version-history":[{"count":5,"href":"https:\/\/sano.science\/index.php\/wp-json\/wp\/v2\/posts\/27535\/revisions"}],"predecessor-version":[{"id":27542,"href":"https:\/\/sano.science\/index.php\/wp-json\/wp\/v2\/posts\/27535\/revisions\/27542"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/sano.science\/index.php\/wp-json\/wp\/v2\/media\/27539"}],"wp:attachment":[{"href":"https:\/\/sano.science\/index.php\/wp-json\/wp\/v2\/media?parent=27535"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/sano.science\/index.php\/wp-json\/wp\/v2\/categories?post=27535"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/sano.science\/index.php\/wp-json\/wp\/v2\/tags?post=27535"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}