{"id":2755,"date":"2025-01-28T09:06:59","date_gmt":"2025-01-28T08:06:59","guid":{"rendered":"https:\/\/wp.unil.ch\/iaunil\/ai-deciphers-websites-to-map-public-health-priorities-around-the-world\/"},"modified":"2025-12-01T10:47:46","modified_gmt":"2025-12-01T09:47:46","slug":"ai-deciphers-websites-to-map-public-health-priorities-around-the-world","status":"publish","type":"post","link":"https:\/\/wp.unil.ch\/iaunil\/en\/ai-deciphers-websites-to-map-public-health-priorities-around-the-world\/","title":{"rendered":"Artificial Intelligence deciphers websites to map public health priorities around the world"},"content":{"rendered":"\n

Original text published on https:\/\/wp.unil.ch\/geoblog\/2024\/03\/des-sites-web-a-la-perception-de-la-sante-publique-dans-diverses-regions-du-monde\/<\/a><\/em><\/p>\n\n

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Drawing on millions of texts from websites and official publications, C\u00e9line Rozenblat and her team used artificial intelligence techniques to explore how health and sustainable development issues are addressed across the globe. Conducted in collaboration with the WHO, this research reveals regional disparities in how urban health is integrated into public policy. Far from being a magical solution, AI is used here as a diagnostic tool\u2014complementary to explanatory approaches\u2014to better understand complex urban systems and support the most vulnerable regions.<\/p>\n<\/div>\n\n\n\n

C\u00e9line Rozenblat used AI for the first time in a project carried out in collaboration with the World Health Organization. The aim of this study was to identify which public or private actions addressed\u2014or failed to address\u2014urban health challenges across different regions of the world, and to examine how these challenges and actions were, or were not, connected to issues of sustainable development.<\/p>\n\n\n\n

\"screenshot\"<\/figure>\n\n\n\n

Millions of publications and institutional websites were analyzed in order to extract their content and classify co-occurring terms. Instead of applying a standard classification, the researchers used topic modeling to identify meaningful word associations. One of the findings shows that actions tend to be more compartmentalized\u2014health issues remaining largely distinct from sustainability issues\u2014in regions where institutions have a long-standing presence, such as Europe and North America. According to C\u00e9line Rozenblat, \u2018The results of this approach highlighted clearer, more streamlined (with fewer parameters), and more robust relationships than those obtained with standard classification models.\u2019<\/p>\n\n\n\n

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Cities change shape or grow \u2013 but why?<\/h3>\n\n\n\n

Currently, Jingyan Yu, a postdoctoral researcher in C\u00e9line Rozenblat\u2019s group, is studying the evolution of urban sprawl worldwide over time. Initially focused solely on the analysis of satellite images (pixel content differences\u2014urban versus non-urban), her models now incorporate AI to qualify the observed changes and are progressively integrating models of urban functioning, in order to understand which parameters most strongly influence the growth or transformation of city forms.<\/p>\n\n\n\n

Combine black box and white box to be able to work in a grey area<\/h3>\n\n\n\n

Currently, Jingyan Yu, a postdoctoral researcher in C\u00e9line Rozenblat\u2019s group, is studying the evolution of urban sprawl worldwide over time. Initially focused solely on the analysis of satellite images (pixel content differences\u2014urban versus non-urban), her models now incorporate AI to qualify the observed changes and are progressively integrating models of urban functioning, in order to understand which parameters most strongly influence the growth or transformation of city forms.<\/p>\n<\/div>\n\n\n\n

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MOOC Healthy urban Systems<\/a><\/h3>\n\n\n\n

According to C\u00e9line Rozenblat, the impact of AI depends on how it is used. It can be applied like following a recipe, which does not generate new knowledge, or it can be leveraged to go beyond established principles. She specifically refers to the approach of deriving equations from the analysis of thousands of data points\u2014a process known as \u2018machine scientists.\u2019 Here, the goal is to let AI test numerous equations within the data and extract the most suitable ones, i.e., those that best capture the relationships among the variables. AI is essential in this context, as it can combine thousands of types of equations that would be impossible to test with standard models. Researchers can then select the equation most consistent with a theoretical framework or compare different equations to foster fruitful debates. C\u00e9line Rozenblat describes this process in a MOOC on the systemic approach to urban health (Healthy Urban Systems), which includes several chapters dedicated to AI.<\/p>\n<\/div>\n\n\n\n

One of the promising uses of AI, according to her, lies in its potential role in supporting developing regions. For example, the enhanced and systematized analysis of satellite imagery through AI can assist in land management in areas where resources for field measurements or data exchange are limited.<\/p>\n\n\n\n

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Professor C\u00e9line Rozenblat, a geographer and specialist in complex systems, mainly studies cities and the various networks that support their functioning.<\/p>\n\n\n\n

Faculty of Geosciences and Environment<\/p>\n\n\n\n

Geo-AI, Information management, Urban Digital Twins, Modelling<\/p>\n\n\n\n

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Profil<\/a><\/div>\n\n\n\n
Publications<\/a><\/div>\n<\/div>\n<\/div>\n\n\n\n
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\"Portrait<\/figure>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

Can we read between the lines of institutional websites to uncover public health priorities? C\u00e9line Rozenblat uses AI to map both actions and silences on a global scale.<\/p>\n","protected":false},"author":108,"featured_media":3274,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_seopress_robots_primary_cat":"","_seopress_titles_title":"","_seopress_titles_desc":"","_seopress_robots_index":"","footnotes":""},"categories":[21],"tags":[],"class_list":{"0":"post-2755","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-research"},"_links":{"self":[{"href":"https:\/\/wp.unil.ch\/iaunil\/en\/wp-json\/wp\/v2\/posts\/2755","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/wp.unil.ch\/iaunil\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/wp.unil.ch\/iaunil\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/wp.unil.ch\/iaunil\/en\/wp-json\/wp\/v2\/users\/108"}],"replies":[{"embeddable":true,"href":"https:\/\/wp.unil.ch\/iaunil\/en\/wp-json\/wp\/v2\/comments?post=2755"}],"version-history":[{"count":4,"href":"https:\/\/wp.unil.ch\/iaunil\/en\/wp-json\/wp\/v2\/posts\/2755\/revisions"}],"predecessor-version":[{"id":3262,"href":"https:\/\/wp.unil.ch\/iaunil\/en\/wp-json\/wp\/v2\/posts\/2755\/revisions\/3262"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/wp.unil.ch\/iaunil\/en\/wp-json\/wp\/v2\/media\/3274"}],"wp:attachment":[{"href":"https:\/\/wp.unil.ch\/iaunil\/en\/wp-json\/wp\/v2\/media?parent=2755"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/wp.unil.ch\/iaunil\/en\/wp-json\/wp\/v2\/categories?post=2755"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/wp.unil.ch\/iaunil\/en\/wp-json\/wp\/v2\/tags?post=2755"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}