{"id":26499,"date":"2025-09-18T18:51:29","date_gmt":"2025-09-18T16:51:29","guid":{"rendered":"https:\/\/sano.science\/?p=26499"},"modified":"2025-10-26T18:55:58","modified_gmt":"2025-10-26T17:55:58","slug":"a-week-in-sheffield-from-principles-to-practice-in-ai%e2%80%91enabled-modelling","status":"publish","type":"post","link":"https:\/\/sano.science\/a-week-in-sheffield-from-principles-to-practice-in-ai%e2%80%91enabled-modelling\/","title":{"rendered":"A week in Sheffield: from principles to practice in AI\u2011enabled modelling"},"content":{"rendered":"\n
In September, a Sano delegation visited a structured training week with the Insigneo Institute in Sheffield to connect machine learning foundations with the realities of modelling and clinical research. The programme\u2014\u201cMachine Learning for Multimodal Research and Healthcare: From Theory to Practice\u201d\u2014was co\u2011delivered by Sano and Insigneo and was open to Insigneo researchers, fostering practical exchange and shared methods across our teams.<\/p>\n\n\n\n
Foundations in ML <\/h2>\n\n\n\n
Day one and two set the groundwork. Jose Sousa (Sano) led an accessible tour of core machine learning concepts, model selection, and evaluation strategies anchored in healthcare use cases. Contributions from Kamil Wo\u017aniak, Jan Argasi\u0144ski, Mahmoud Nasr, Yousef Khan, and Joan Falc\u00f3\u2011Roget broadened the perspective with multimodal pipelines and reproducibility practices, keeping the emphasis on approaches that translated directly into robust workflows.<\/p>\n\n\n\n
Modelling meets AI <\/h2>\n\n\n\n
Midweek turned to mechanistic models and their synergy with AI. Ian Halliday (Insigneo) outlined where physics\u2011based models excel and where they face limits, then showed how data\u2011driven methods can extend their reach\u2014from emulators that accelerate exploration to physics\u2011informed neural networks that encode governing constraints. The message was pragmatic: AI complemented modelling, strengthening scale, uncertainty handling, and time\u2011to\u2011insight.<\/p>\n\n\n\n
Case study: CACTUS x aneurysms <\/h2>\n\n\n\n
Thursday offered a concrete bridge between theory and application. In a joint case study, Albert Marzo (Insigneo) and Jose Sousa demonstrated how Sano\u2019s explainable ML framework CACTUS integrated with cerebrovascular aneurysm data. They walked through data preparation, training and validation, emulator design, and interpretability\u2014illustrating a transparent path from experimental evidence to credible, decision\u2011supportive analysis.<\/p>\n\n\n\n
Peer consultations <\/h2>\n\n\n\n
Wednesday afternoon highlighted collaboration in action. Sano researchers and Insigneo colleagues met for expert\u2011to\u2011expert consultations on ongoing projects\u2014testing assumptions, refining validation strategies, and aligning methods with clinical context. The exchange surfaced clear next steps across imaging, cardiovascular and neuro applications, and workflow automation, pointing to where hybrid modelling\u2011plus\u2011ML could deliver near\u2011term impact.<\/p>\n\n\n\n
Panel and takeaways <\/h2>\n\n\n\n
The week concluded with a forward\u2011looking panel featuring Enrico Dall\u2019Ara, Shannon Li, and Lingzhong Guo on integrating modelling and AI in practice. Discussions centred on verification and validation, reproducibility across pipelines, and building clinical credibility\u2014what evidence is needed and how to maintain trust as models and data evolve.<\/p>\n\n\n\n
Beyond the seminar room <\/h2>\n\n\n\n
Beyond the seminar rooms, the visit strengthened rapport and collaboration. An atmospheric dinner at the stylish Halifax Hall provided a graceful backdrop for continuing conversations, complemented by a classic pie supper at the University Arms and a spirited go\u2011kart session that closed the week on a high.<\/p>\n\n\n\n
What it means for Sano <\/h2>\n\n\n\n
For Sano, the Sheffield week advanced a shared curriculum with Insigneo, produced ready\u2011to\u2011adapt example pipelines\u2014from emulators to physics\u2011informed learning\u2014and deepened collaboration around CACTUS\u2011enabled analyses and multimodal workflows. Above all, it reaffirmed a joint commitment: pairing high\u2011fidelity models with modern machine learning to deliver explainable, scalable tools that clinicians can trust.<\/p>\n\n\n\n
A road well travelled<\/h2>\n\n\n\n
As a fitting coda, the road to Sheffield unfolded through quietly beautiful scenes\u2014rolling hills, green pastures, and flocks of grazing sheep\u2014reminding us that rigorous science can travel hand in hand with moments of simple, restorative landscape.<\/p>\n\n\n\n
<\/p>\n\n\n\n<\/figure>\n","protected":false},"excerpt":"Sano\u2019s delegation joined Insigneo for a focused training week that paired machine learning with mechanistic modelling to advance credible, clinician\u2011ready tools.","author":8,"featured_media":26500,"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-26499","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized"],"yoast_head":"\nA week in Sheffield: from principles to practice in AI\u2011enabled modelling - Centre for Computational Personalized Medicine<\/title>\n<meta name=\"description\" content=\"Sano\u2019s delegation joined Insigneo in Sheffield for a training week linking machine learning and modelling\u2014case studies, peer consultations, and clinical credibility.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/sano.science\/a-week-in-sheffield-from-principles-to-practice-in-ai\u2011enabled-modelling\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"A week in Sheffield: from principles to practice in AI\u2011enabled modelling\" \/>\n<meta property=\"og:description\" content=\"Sano\u2019s delegation joined Insigneo in Sheffield for a training week linking machine learning and modelling\u2014case studies, peer consultations, and clinical credibility.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/sano.science\/a-week-in-sheffield-from-principles-to-practice-in-ai\u2011enabled-modelling\/\" \/>\n<meta property=\"og:site_name\" content=\"Centre for Computational Personalized Medicine\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/sano.science\/\" \/>\n<meta property=\"article:published_time\" content=\"2025-09-18T16:51:29+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2025-10-26T17:55:58+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/sano.science\/wp-content\/uploads\/2025\/10\/Sheffield_4-scaled.jpeg\" \/>\n\t<meta property=\"og:image:width\" content=\"2560\" \/>\n\t<meta property=\"og:image:height\" content=\"1920\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"Sano\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@sanoscience\" \/>\n<meta name=\"twitter:site\" content=\"@sanoscience\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Sano\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"3 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\\\/\\\/sano.science\\\/a-week-in-sheffield-from-principles-to-practice-in-ai%e2%80%91enabled-modelling\\\/#article\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/sano.science\\\/a-week-in-sheffield-from-principles-to-practice-in-ai%e2%80%91enabled-modelling\\\/\"},\"author\":{\"name\":\"Sano\",\"@id\":\"https:\\\/\\\/sano.science\\\/#\\\/schema\\\/person\\\/561b69b48b6a8f7904aed06df5d03c98\"},\"headline\":\"A week in Sheffield: from principles to practice in AI\u2011enabled modelling\",\"datePublished\":\"2025-09-18T16:51:29+00:00\",\"dateModified\":\"2025-10-26T17:55:58+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\\\/\\\/sano.science\\\/a-week-in-sheffield-from-principles-to-practice-in-ai%e2%80%91enabled-modelling\\\/\"},\"wordCount\":542,\"publisher\":{\"@id\":\"https:\\\/\\\/sano.science\\\/#organization\"},\"image\":{\"@id\":\"https:\\\/\\\/sano.science\\\/a-week-in-sheffield-from-principles-to-practice-in-ai%e2%80%91enabled-modelling\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/sano.science\\\/wp-content\\\/uploads\\\/2025\\\/10\\\/Sheffield_4-scaled.jpeg\",\"inLanguage\":\"en-US\"},{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/sano.science\\\/a-week-in-sheffield-from-principles-to-practice-in-ai%e2%80%91enabled-modelling\\\/\",\"url\":\"https:\\\/\\\/sano.science\\\/a-week-in-sheffield-from-principles-to-practice-in-ai%e2%80%91enabled-modelling\\\/\",\"name\":\"A week in Sheffield: from principles to practice in AI\u2011enabled modelling - 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The programme\u2014\u201cMachine Learning for Multimodal Research and Healthcare: From Theory to Practice\u201d\u2014was co\u2011delivered by Sano and Insigneo and was open to Insigneo researchers, fostering practical exchange and shared methods across our teams.<\/p>\n","innerContent":["\n<p class=\" eplus-wrapper\">In September, a Sano delegation visited a structured training week with the Insigneo Institute in Sheffield to connect machine learning foundations with the realities of modelling and clinical research. The programme\u2014\u201cMachine Learning for Multimodal Research and Healthcare: From Theory to Practice\u201d\u2014was co\u2011delivered by Sano and Insigneo and was open to Insigneo researchers, fostering practical exchange and shared methods across our teams.<\/p>\n"]},{"blockName":"core\/heading","attrs":{"epAnimationGeneratedClass":"edplus_anim-5Yg820","epGeneratedClass":"eplus-wrapper"},"innerBlocks":[],"innerHTML":"\n<h2 class=\"wp-block-heading eplus-wrapper\" id=\"h-foundations-in-ml\">Foundations in ML<br><\/h2>\n","innerContent":["\n<h2 class=\"wp-block-heading eplus-wrapper\" id=\"h-foundations-in-ml\">Foundations in ML<br><\/h2>\n"]},{"blockName":"core\/paragraph","attrs":{"epAnimationGeneratedClass":"edplus_anim-2odrKX","epGeneratedClass":"eplus-wrapper"},"innerBlocks":[],"innerHTML":"\n<p class=\" eplus-wrapper\">Day one and two set the groundwork. Jose Sousa (Sano) led an accessible tour of core machine learning concepts, model selection, and evaluation strategies anchored in healthcare use cases. Contributions from Kamil Wo\u017aniak, Jan Argasi\u0144ski, Mahmoud Nasr, Yousef Khan, and Joan Falc\u00f3\u2011Roget broadened the perspective with multimodal pipelines and reproducibility practices, keeping the emphasis on approaches that translated directly into robust workflows.<\/p>\n","innerContent":["\n<p class=\" eplus-wrapper\">Day one and two set the groundwork. Jose Sousa (Sano) led an accessible tour of core machine learning concepts, model selection, and evaluation strategies anchored in healthcare use cases. Contributions from Kamil Wo\u017aniak, Jan Argasi\u0144ski, Mahmoud Nasr, Yousef Khan, and Joan Falc\u00f3\u2011Roget broadened the perspective with multimodal pipelines and reproducibility practices, keeping the emphasis on approaches that translated directly into robust workflows.<\/p>\n"]},{"blockName":"core\/heading","attrs":{"epAnimationGeneratedClass":"edplus_anim-UpoPMC","epGeneratedClass":"eplus-wrapper"},"innerBlocks":[],"innerHTML":"\n<h2 class=\"wp-block-heading eplus-wrapper\" id=\"h-modelling-meets-ai\">Modelling meets AI<br><\/h2>\n","innerContent":["\n<h2 class=\"wp-block-heading eplus-wrapper\" id=\"h-modelling-meets-ai\">Modelling meets AI<br><\/h2>\n"]},{"blockName":"core\/paragraph","attrs":{"epAnimationGeneratedClass":"edplus_anim-MaukLC","epGeneratedClass":"eplus-wrapper"},"innerBlocks":[],"innerHTML":"\n<p class=\" eplus-wrapper\">Midweek turned to mechanistic models and their synergy with AI. Ian Halliday (Insigneo) outlined where physics\u2011based models excel and where they face limits, then showed how data\u2011driven methods can extend their reach\u2014from emulators that accelerate exploration to physics\u2011informed neural networks that encode governing constraints. The message was pragmatic: AI complemented modelling, strengthening scale, uncertainty handling, and time\u2011to\u2011insight.<\/p>\n","innerContent":["\n<p class=\" eplus-wrapper\">Midweek turned to mechanistic models and their synergy with AI. Ian Halliday (Insigneo) outlined where physics\u2011based models excel and where they face limits, then showed how data\u2011driven methods can extend their reach\u2014from emulators that accelerate exploration to physics\u2011informed neural networks that encode governing constraints. The message was pragmatic: AI complemented modelling, strengthening scale, uncertainty handling, and time\u2011to\u2011insight.<\/p>\n"]},{"blockName":"core\/heading","attrs":{"epAnimationGeneratedClass":"edplus_anim-rq4TVJ","epGeneratedClass":"eplus-wrapper"},"innerBlocks":[],"innerHTML":"\n<h2 class=\"wp-block-heading eplus-wrapper\" id=\"h-case-study-cactus-x-aneurysms\">Case study: CACTUS x aneurysms<br><\/h2>\n","innerContent":["\n<h2 class=\"wp-block-heading eplus-wrapper\" id=\"h-case-study-cactus-x-aneurysms\">Case study: CACTUS x aneurysms<br><\/h2>\n"]},{"blockName":"core\/paragraph","attrs":{"epAnimationGeneratedClass":"edplus_anim-ATTgZN","epGeneratedClass":"eplus-wrapper"},"innerBlocks":[],"innerHTML":"\n<p class=\" eplus-wrapper\">Thursday offered a concrete bridge between theory and application. In a joint case study, Albert Marzo (Insigneo) and Jose Sousa demonstrated how Sano\u2019s explainable ML framework CACTUS integrated with cerebrovascular aneurysm data. They walked through data preparation, training and validation, emulator design, and interpretability\u2014illustrating a transparent path from experimental evidence to credible, decision\u2011supportive analysis.<\/p>\n","innerContent":["\n<p class=\" eplus-wrapper\">Thursday offered a concrete bridge between theory and application. In a joint case study, Albert Marzo (Insigneo) and Jose Sousa demonstrated how Sano\u2019s explainable ML framework CACTUS integrated with cerebrovascular aneurysm data. They walked through data preparation, training and validation, emulator design, and interpretability\u2014illustrating a transparent path from experimental evidence to credible, decision\u2011supportive analysis.<\/p>\n"]},{"blockName":"core\/heading","attrs":{"epAnimationGeneratedClass":"edplus_anim-2I7sOa","epGeneratedClass":"eplus-wrapper"},"innerBlocks":[],"innerHTML":"\n<h2 class=\"wp-block-heading eplus-wrapper\" id=\"h-peer-consultations\">Peer consultations<br><\/h2>\n","innerContent":["\n<h2 class=\"wp-block-heading eplus-wrapper\" id=\"h-peer-consultations\">Peer consultations<br><\/h2>\n"]},{"blockName":"core\/paragraph","attrs":{"epAnimationGeneratedClass":"edplus_anim-XdXoc6","epGeneratedClass":"eplus-wrapper"},"innerBlocks":[],"innerHTML":"\n<p class=\" eplus-wrapper\">Wednesday afternoon highlighted collaboration in action. Sano researchers and Insigneo colleagues met for expert\u2011to\u2011expert consultations on ongoing projects\u2014testing assumptions, refining validation strategies, and aligning methods with clinical context. The exchange surfaced clear next steps across imaging, cardiovascular and neuro applications, and workflow automation, pointing to where hybrid modelling\u2011plus\u2011ML could deliver near\u2011term impact.<\/p>\n","innerContent":["\n<p class=\" eplus-wrapper\">Wednesday afternoon highlighted collaboration in action. Sano researchers and Insigneo colleagues met for expert\u2011to\u2011expert consultations on ongoing projects\u2014testing assumptions, refining validation strategies, and aligning methods with clinical context. The exchange surfaced clear next steps across imaging, cardiovascular and neuro applications, and workflow automation, pointing to where hybrid modelling\u2011plus\u2011ML could deliver near\u2011term impact.<\/p>\n"]},{"blockName":"core\/heading","attrs":{"epAnimationGeneratedClass":"edplus_anim-aSDnPZ","epGeneratedClass":"eplus-wrapper"},"innerBlocks":[],"innerHTML":"\n<h2 class=\"wp-block-heading eplus-wrapper\" id=\"h-panel-and-takeaways\">Panel and takeaways<br><\/h2>\n","innerContent":["\n<h2 class=\"wp-block-heading eplus-wrapper\" id=\"h-panel-and-takeaways\">Panel and takeaways<br><\/h2>\n"]},{"blockName":"core\/paragraph","attrs":{"epAnimationGeneratedClass":"edplus_anim-AR6EEO","epGeneratedClass":"eplus-wrapper"},"innerBlocks":[],"innerHTML":"\n<p class=\" eplus-wrapper\">The week concluded with a forward\u2011looking panel featuring Enrico Dall\u2019Ara, Shannon Li, and Lingzhong Guo on integrating modelling and AI in practice. Discussions centred on verification and validation, reproducibility across pipelines, and building clinical credibility\u2014what evidence is needed and how to maintain trust as models and data evolve.<\/p>\n","innerContent":["\n<p class=\" eplus-wrapper\">The week concluded with a forward\u2011looking panel featuring Enrico Dall\u2019Ara, Shannon Li, and Lingzhong Guo on integrating modelling and AI in practice. Discussions centred on verification and validation, reproducibility across pipelines, and building clinical credibility\u2014what evidence is needed and how to maintain trust as models and data evolve.<\/p>\n"]},{"blockName":"core\/heading","attrs":{"epAnimationGeneratedClass":"edplus_anim-fGtQ36","epGeneratedClass":"eplus-wrapper"},"innerBlocks":[],"innerHTML":"\n<h2 class=\"wp-block-heading eplus-wrapper\" id=\"h-beyond-the-seminar-room\">Beyond the seminar room<br><\/h2>\n","innerContent":["\n<h2 class=\"wp-block-heading eplus-wrapper\" id=\"h-beyond-the-seminar-room\">Beyond the seminar room<br><\/h2>\n"]},{"blockName":"core\/paragraph","attrs":{"epAnimationGeneratedClass":"edplus_anim-tkUeCb","epGeneratedClass":"eplus-wrapper"},"innerBlocks":[],"innerHTML":"\n<p class=\" eplus-wrapper\">Beyond the seminar rooms, the visit strengthened rapport and collaboration. An atmospheric dinner at the stylish Halifax Hall provided a graceful backdrop for continuing conversations, complemented by a classic pie supper at the University Arms and a spirited go\u2011kart session that closed the week on a high.<\/p>\n","innerContent":["\n<p class=\" eplus-wrapper\">Beyond the seminar rooms, the visit strengthened rapport and collaboration. An atmospheric dinner at the stylish Halifax Hall provided a graceful backdrop for continuing conversations, complemented by a classic pie supper at the University Arms and a spirited go\u2011kart session that closed the week on a high.<\/p>\n"]},{"blockName":"core\/heading","attrs":{"epAnimationGeneratedClass":"edplus_anim-QQnD54","epGeneratedClass":"eplus-wrapper"},"innerBlocks":[],"innerHTML":"\n<h2 class=\"wp-block-heading eplus-wrapper\" id=\"h-what-it-means-for-sano\">What it means for Sano<br><\/h2>\n","innerContent":["\n<h2 class=\"wp-block-heading eplus-wrapper\" id=\"h-what-it-means-for-sano\">What it means for Sano<br><\/h2>\n"]},{"blockName":"core\/paragraph","attrs":{"epAnimationGeneratedClass":"edplus_anim-C16HHf","epGeneratedClass":"eplus-wrapper"},"innerBlocks":[],"innerHTML":"\n<p class=\" eplus-wrapper\">For Sano, the Sheffield week advanced a shared curriculum with Insigneo, produced ready\u2011to\u2011adapt example pipelines\u2014from emulators to physics\u2011informed learning\u2014and deepened collaboration around CACTUS\u2011enabled analyses and multimodal workflows. Above all, it reaffirmed a joint commitment: pairing high\u2011fidelity models with modern machine learning to deliver explainable, scalable tools that clinicians can trust.<\/p>\n","innerContent":["\n<p class=\" eplus-wrapper\">For Sano, the Sheffield week advanced a shared curriculum with Insigneo, produced ready\u2011to\u2011adapt example pipelines\u2014from emulators to physics\u2011informed learning\u2014and deepened collaboration around CACTUS\u2011enabled analyses and multimodal workflows. Above all, it reaffirmed a joint commitment: pairing high\u2011fidelity models with modern machine learning to deliver explainable, scalable tools that clinicians can trust.<\/p>\n"]},{"blockName":"core\/heading","attrs":{"epAnimationGeneratedClass":"edplus_anim-KApuJb","epGeneratedClass":"eplus-wrapper"},"innerBlocks":[],"innerHTML":"\n<h2 class=\"wp-block-heading eplus-wrapper\" id=\"h-a-road-well-travelled\">A road well travelled<\/h2>\n","innerContent":["\n<h2 class=\"wp-block-heading eplus-wrapper\" id=\"h-a-road-well-travelled\">A road well travelled<\/h2>\n"]},{"blockName":"core\/paragraph","attrs":{"epAnimationGeneratedClass":"edplus_anim-FsAHlO","epGeneratedClass":"eplus-wrapper"},"innerBlocks":[],"innerHTML":"\n<p class=\" eplus-wrapper\">As a fitting coda, the road to Sheffield unfolded through quietly beautiful scenes\u2014rolling hills, green pastures, and flocks of grazing sheep\u2014reminding us that rigorous science can travel hand in hand with moments of simple, restorative landscape.<\/p>\n","innerContent":["\n<p class=\" eplus-wrapper\">As a fitting coda, the road to Sheffield unfolded through quietly beautiful scenes\u2014rolling hills, green pastures, and flocks of grazing sheep\u2014reminding us that rigorous science can travel hand in hand with moments of simple, restorative landscape.<\/p>\n"]},{"blockName":"core\/paragraph","attrs":{"epAnimationGeneratedClass":"edplus_anim-uEeWcj","epGeneratedClass":"eplus-wrapper"},"innerBlocks":[],"innerHTML":"\n<p class=\" eplus-wrapper\"><\/p>\n","innerContent":["\n<p class=\" eplus-wrapper\"><\/p>\n"]},{"blockName":"core\/image","attrs":{"id":26501,"sizeSlug":"large","linkDestination":"none","epAnimationGeneratedClass":"edplus_anim-6stIRf","epGeneratedClass":"eplus-wrapper"},"innerBlocks":[],"innerHTML":"\n<figure class=\"wp-block-image size-large eplus-wrapper\"><img src=\"https:\/\/sano.science\/wp-content\/uploads\/2025\/10\/Sheffield_10-1024x768.jpg\" alt=\"\" class=\"wp-image-26501\"\/><\/figure>\n","innerContent":["\n<figure class=\"wp-block-image size-large eplus-wrapper\"><img src=\"https:\/\/sano.science\/wp-content\/uploads\/2025\/10\/Sheffield_10-1024x768.jpg\" alt=\"\" class=\"wp-image-26501\"\/><\/figure>\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\/10\/Sheffield_4-1024x768.jpeg"},"main_category":{"name":"Uncategorized"},"prev_page":{"slug":"sano-running-team-shines-at-poland-business-run-2025"},"next_page":{"slug":"dr-eng-marek-wodzinski-named-finalist-of-the-25th-polityka-science-awards-collaboration-with-sano-coming-soon"},"_links":{"self":[{"href":"https:\/\/sano.science\/index.php\/wp-json\/wp\/v2\/posts\/26499","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=26499"}],"version-history":[{"count":1,"href":"https:\/\/sano.science\/index.php\/wp-json\/wp\/v2\/posts\/26499\/revisions"}],"predecessor-version":[{"id":26502,"href":"https:\/\/sano.science\/index.php\/wp-json\/wp\/v2\/posts\/26499\/revisions\/26502"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/sano.science\/index.php\/wp-json\/wp\/v2\/media\/26500"}],"wp:attachment":[{"href":"https:\/\/sano.science\/index.php\/wp-json\/wp\/v2\/media?parent=26499"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/sano.science\/index.php\/wp-json\/wp\/v2\/categories?post=26499"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/sano.science\/index.php\/wp-json\/wp\/v2\/tags?post=26499"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
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<\/figure>\n","protected":false},"excerpt":"Sano\u2019s delegation joined Insigneo for a focused training week that paired machine learning with mechanistic modelling to advance credible, clinician\u2011ready tools.","author":8,"featured_media":26500,"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-26499","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized"],"yoast_head":"\n