{"id":9180,"date":"2025-09-17T15:19:58","date_gmt":"2025-09-17T15:19:58","guid":{"rendered":"https:\/\/placedesnations.org\/index.php\/2025\/09\/17\/ai-can-forecast-your-future-health-just-like-the-weather\/"},"modified":"2025-09-17T15:19:58","modified_gmt":"2025-09-17T15:19:58","slug":"ai-can-forecast-your-future-health-just-like-the-weather","status":"publish","type":"post","link":"https:\/\/placedesnations.org\/index.php\/2025\/09\/17\/ai-can-forecast-your-future-health-just-like-the-weather\/","title":{"rendered":"AI can forecast your future health \u2013 just like the weather"},"content":{"rendered":"<p>Artificial intelligence can predict people&rsquo;s health problems over a decade into the future, say scientists.<\/p>\n<p>The technology has learned to spot patterns in people&rsquo;s medical records to calculate their risk of more than 1,000 diseases.<\/p>\n<p>The researchers say it is like a weather forecast that anticipates a 70% chance of rain \u2013 but for human health.<\/p>\n<p>Their vision is to use the AI model to spot high-risk patients to prevent disease and to help hospitals understand demand in their area, years ahead of time.<\/p>\n<p>The model \u2013 called Delphi-2M &#8211; uses similar technology to well-known AI chatbots like ChatGPT.<\/p>\n<p>AI chatbots are trained to understand patterns of language so they can predict the sequence of words in a sentence.<\/p>\n<p>Delphi-2M has been trained to find patterns in anonymous medical records so it can predict what comes next and when.<\/p>\n<p>It doesn&rsquo;t predict exact dates, like a heart attack on October 1, but instead estimates the likelihood of 1,231 diseases.<\/p>\n<p>\u00ab\u00a0So, just like weather, where we could have a 70% chance of rain, we can do that for healthcare,\u00a0\u00bb Prof Ewan Birney, the interim executive director of the European Molecular Biology Laboratory, told me.<\/p>\n<p>\u00ab\u00a0And we can do that not just for one disease, but all diseases at the same time &#8211; we&rsquo;ve never been able to do that before. I&rsquo;m excited,\u00a0\u00bb he said.<\/p>\n<p>The AI model was initially developed using anonymous UK data &#8211; including hospital admissions, GP records and lifestyle habits such as smoking &#8211; collected from more than 400,000 people as part of the UK Biobank research project.<\/p>\n<p>The model was then tested to see if its predictions stacked up using data from other Biobank participants, and then with 1.9 million people&rsquo;s medical records in Denmark.<\/p>\n<p>\u00ab\u00a0It&rsquo;s good, it&rsquo;s really good in Denmark,\u00a0\u00bb says Prof Birney.<\/p>\n<p>\u00ab\u00a0If our model says it&rsquo;s a one-in-10 risk for the next year, it really does seem like it turns out to be one in 10.\u00a0\u00bb<\/p>\n<p>The model is best at predicting diseases like type 2 diabetes, heart attacks and sepsis that have a clear disease progression, rather than more random events like infections.<\/p>\n<p>People are already offered a cholesterol-lowering statin based on a calculation of their risk of a heart attack or stroke.<\/p>\n<p>The AI tool is not ready for clinical use, but the plan is to use it in a similar way, to spot high-risk patients while there is an opportunity to intervene early and prevent disease.<\/p>\n<p>This could include medicines or specific lifestyle advice &#8211; such as people likely to develop some liver disorders benefitting from cutting back their alcohol intake more than the general population.<\/p>\n<p>The artificial intelligence could also help inform disease-screening programmes and  analyse all the healthcare records in an area to anticipate demand &#8211; such as how many heart attacks a year there will be in Norwich in 2030, to help plan resources.<\/p>\n<p>\u00ab\u00a0This is the beginning of a new way to understand human health and disease progression,\u00a0\u00bb said Prof Moritz Gerstung, head of the division of AI in oncology at DKFZ, the German Cancer Research Centre.<\/p>\n<p>He added: \u00ab\u00a0Generative models such as ours could one day help personalise care and anticipate healthcare needs at scale.\u00a0\u00bb<\/p>\n<p>The AI model, described in the scientific journal Nature, needs refining and testing before it is used clinically.<\/p>\n<p>There are also potential biases as it was built from UK Biobank data which is drawn mostly from people aged 40 to 70, rather than the whole population.<\/p>\n<p>The model is now being upgraded to account for more medical data such as imaging, genetics and blood analysis.<\/p>\n<p>But Prof Birney says: \u00ab\u00a0Just to stress, this is research \u2013 everything needs to be tested and well-regulated and thought about before it&rsquo;s used, but the technology is here to make these kinds of predictions.\u00a0\u00bb<\/p>\n<p>He anticipates it will follow a similar path to the use of genomics in healthcare where it took a decade to go from scientists being confident in the technology to healthcare being able to use it routinely.<\/p>\n<p>The study was a collaboration between the European Molecular Biology Laboratory, the German Cancer Research Centre (DKFZ) and the University of Copenhagen.<\/p>\n<p>Prof Gustavo Sudre, a neuroimaging and AI researcher at King&rsquo;s College London, commented: \u00ab\u00a0This research looks to be a significant step towards scalable, interpretable, and \u2013 most importantly \u2013 ethically responsible form of predictive modelling in medicine.\u00a0\u00bb<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Artificial intelligence can predict people&rsquo;s health problems over a decade into the future, say scientists. The technology has learned to spot patterns in people&rsquo;s medical records to calculate their risk of more than 1,000 diseases. The researchers say it is like a weather forecast that anticipates a 70% chance of rain \u2013 but for human [&hellip;]<\/p>\n","protected":false},"author":0,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":{"0":"post-9180","1":"post","2":"type-post","3":"status-publish","4":"format-standard","6":"category-uncategorized"},"_links":{"self":[{"href":"https:\/\/placedesnations.org\/index.php\/wp-json\/wp\/v2\/posts\/9180","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/placedesnations.org\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/placedesnations.org\/index.php\/wp-json\/wp\/v2\/types\/post"}],"replies":[{"embeddable":true,"href":"https:\/\/placedesnations.org\/index.php\/wp-json\/wp\/v2\/comments?post=9180"}],"version-history":[{"count":0,"href":"https:\/\/placedesnations.org\/index.php\/wp-json\/wp\/v2\/posts\/9180\/revisions"}],"wp:attachment":[{"href":"https:\/\/placedesnations.org\/index.php\/wp-json\/wp\/v2\/media?parent=9180"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/placedesnations.org\/index.php\/wp-json\/wp\/v2\/categories?post=9180"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/placedesnations.org\/index.php\/wp-json\/wp\/v2\/tags?post=9180"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}