{"id":30616,"date":"2025-10-15T16:31:08","date_gmt":"2025-10-15T16:31:08","guid":{"rendered":"https:\/\/www.tun.com\/home\/?p=30616"},"modified":"2025-10-15T16:31:10","modified_gmt":"2025-10-15T16:31:10","slug":"new-ai-system-spots-hidden-patterns-in-electronic-health-records","status":"publish","type":"post","link":"https:\/\/www.tun.com\/home\/new-ai-system-spots-hidden-patterns-in-electronic-health-records\/","title":{"rendered":"New AI System Spots Hidden Patterns in Electronic Health Records"},"content":{"rendered":"\n<div class=\"wp-block-group\"><div class=\"wp-block-group__inner-container is-layout-constrained wp-block-group-is-layout-constrained\">\n<div class=\"wp-block-uagb-blockquote uagb-block-e7eb3fc3 uagb-blockquote__skin-border uagb-blockquote__stack-img-none\"><blockquote class=\"uagb-blockquote\"><div class=\"uagb-blockquote__content\">Mount Sinai researchers unveil InfEHR, an AI system that links unconnected medical events in electronic health records, enhancing diagnostic accuracy and uncovering hidden health patterns. This breakthrough promises significant advancements in personalized medicine and patient care.<\/div><footer><div class=\"uagb-blockquote__author-wrap uagb-blockquote__author-at-left\"><\/div><\/footer><\/blockquote><\/div>\n\n\n\n<div class=\"wp-block-group is-content-justification-space-between is-nowrap is-layout-flex wp-container-core-group-is-layout-0dfbf163 wp-block-group-is-layout-flex\"><div style=\"font-size:16px;\" class=\"has-text-align-left wp-block-post-author\"><div class=\"wp-block-post-author__content\"><p class=\"wp-block-post-author__name\">The University Network<\/p><\/div><\/div>\n\n\n<div class=\"wp-block-uagb-social-share uagb-social-share__outer-wrap uagb-social-share__layout-horizontal uagb-block-ee584a31\">\n<div class=\"wp-block-uagb-social-share-child uagb-ss-repeater uagb-ss__wrapper uagb-block-ec619ce7\"><span class=\"uagb-ss__link\" data-href=\"https:\/\/www.facebook.com\/sharer.php?u=\" tabindex=\"0\" role=\"button\" aria-label=\"facebook\"><span class=\"uagb-ss__source-wrap\"><span class=\"uagb-ss__source-icon\"><svg xmlns=\"https:\/\/www.w3.org\/2000\/svg\" viewBox=\"0 0 512 512\"><path d=\"M504 256C504 119 393 8 256 8S8 119 8 256c0 123.8 90.69 226.4 209.3 245V327.7h-63V256h63v-54.64c0-62.15 37-96.48 93.67-96.48 27.14 0 55.52 4.84 55.52 4.84v61h-31.28c-30.8 0-40.41 19.12-40.41 38.73V256h68.78l-11 71.69h-57.78V501C413.3 482.4 504 379.8 504 256z\"><\/path><\/svg><\/span><\/span><\/span><\/div>\n\n\n\n<div class=\"wp-block-uagb-social-share-child uagb-ss-repeater uagb-ss__wrapper uagb-block-32d99934\"><span class=\"uagb-ss__link\" data-href=\"https:\/\/twitter.com\/share?url=\" tabindex=\"0\" role=\"button\" aria-label=\"twitter\"><span class=\"uagb-ss__source-wrap\"><span class=\"uagb-ss__source-icon\"><svg xmlns=\"https:\/\/www.w3.org\/2000\/svg\" viewBox=\"0 0 512 512\"><path d=\"M389.2 48h70.6L305.6 224.2 487 464H345L233.7 318.6 106.5 464H35.8L200.7 275.5 26.8 48H172.4L272.9 180.9 389.2 48zM364.4 421.8h39.1L151.1 88h-42L364.4 421.8z\"><\/path><\/svg><\/span><\/span><\/span><\/div>\n\n\n\n<div class=\"wp-block-uagb-social-share-child uagb-ss-repeater uagb-ss__wrapper uagb-block-1d136f14\"><span class=\"uagb-ss__link\" data-href=\"https:\/\/www.linkedin.com\/shareArticle?url=\" tabindex=\"0\" role=\"button\" aria-label=\"linkedin\"><span class=\"uagb-ss__source-wrap\"><span class=\"uagb-ss__source-icon\"><svg xmlns=\"https:\/\/www.w3.org\/2000\/svg\" viewBox=\"0 0 448 512\"><path d=\"M416 32H31.9C14.3 32 0 46.5 0 64.3v383.4C0 465.5 14.3 480 31.9 480H416c17.6 0 32-14.5 32-32.3V64.3c0-17.8-14.4-32.3-32-32.3zM135.4 416H69V202.2h66.5V416zm-33.2-243c-21.3 0-38.5-17.3-38.5-38.5S80.9 96 102.2 96c21.2 0 38.5 17.3 38.5 38.5 0 21.3-17.2 38.5-38.5 38.5zm282.1 243h-66.4V312c0-24.8-.5-56.7-34.5-56.7-34.6 0-39.9 27-39.9 54.9V416h-66.4V202.2h63.7v29.2h.9c8.9-16.8 30.6-34.5 62.9-34.5 67.2 0 79.7 44.3 79.7 101.9V416z\"><\/path><\/svg><\/span><\/span><\/span><\/div>\n<\/div>\n<\/div>\n<\/div><\/div>\n\n\n\n<p>A breakthrough in artificial intelligence could soon revolutionize how doctors diagnose diseases. Researchers at the Icahn School of Medicine at Mount Sinai and their collaborators have developed InfEHR, an AI system that connects disparate medical events over time. This innovative technology is capable of revealing hidden patterns within electronic health records (EHRs), transforming millions of fragmented data points into actionable diagnostic insights.<\/p>\n\n\n\n<p>The study, <a href=\"https:\/\/www.nature.com\/articles\/s41467-025-63366-6\" target=\"_blank\" rel=\"noopener\" title=\"\">published<\/a> on Sept. 26 in Nature Communications, highlights InfEHR&#8217;s ability to personalize diagnostics. Rather than following a generic diagnostic process, InfEHR customizes its analysis for each patient by constructing a network from individual medical events. <\/p>\n\n\n\n<p>This approach allows the AI to not only provide personalized answers but also pose personalized questions, significantly enhancing the diagnostic process.<\/p>\n\n\n\n<p>&#8220;We were intrigued by how often the system rediscovered patterns that clinicians suspected but couldn&#8217;t act on because the evidence wasn&#8217;t fully established,&#8221; senior corresponding author\u00a0Girish N. Nadkarni, the chair of the\u00a0Windreich Department of Artificial Intelligence and Human Health, director of the\u00a0Hasso Plattner Institute for Digital Health, the Irene and Dr. Arthur M. Fishberg Professor of Medicine at the Icahn School of Medicine at Mount Sinai, and the chief AI officer of the Mount Sinai Health System, said in a news release. &#8220;By quantifying those intuitions, InfEHR gives us a way to validate what was previously just a hunch and opens the door to entirely new discoveries.&#8221;\u202f\u00a0<\/p>\n\n\n\n<p>In the study, the InfEHR system analyzed deidentified electronic records from Mount Sinai Hospital in New York and UC Irvine in California. The AI transformed each patient&#8217;s medical timeline into a network illustrating how various medical events were connected over time. By scrutinizing multiple such networks, InfEHR learned to detect patterns typically associated with underlying conditions.<\/p>\n\n\n\n<p>Cost efficiency and accuracy are notable advantages of InfEHR. The AI system doesn&#8217;t require extensive training data, instead learning directly from patient records. This adaptability allows it to work effectively across different hospital systems and populations.<\/p>\n\n\n\n<p>For instance, InfEHR was significantly more effective in identifying newborns with sepsis, a life-threatening condition, compared to conventional methods. It was 12-16 times more likely to flag affected infants. <\/p>\n\n\n\n<p>Similarly, the system identified patients at risk for postoperative kidney injury 4-7 times more effectively than current practices.<\/p>\n\n\n\n<p>One of the standout features of InfEHR is its ability to indicate uncertainty. It can respond \u201cnot sure\u201d when there is insufficient data, a key safety feature that addresses a major drawback of traditional AI, which might provide incorrect answers with unwarranted confidence.<\/p>\n\n\n\n<p>\u201cTraditional AI asks, \u2018Does this patient resemble others with the disease?\u2019 InfEHR takes a different approach: \u2018Could this patient\u2019s unique medical trajectory result from an underlying disease process?\u2019 It\u2019s the difference between simply matching patterns and uncovering causation,\u201d added lead author Justin Kauffman, a senior data scientist in the Windreich Department of Artificial Intelligence and Human Health at the Icahn School of Medicine.\u00a0<\/p>\n\n\n\n<p>Looking ahead, the research team plans to extend InfEHR&#8217;s applications, such as personalizing treatment decisions by integrating clinical trial data. This could bridge gaps between trial-based research and patient care in diverse clinical settings.<\/p>\n\n\n\n<p>\u201cClinical trials often focus on specific populations, while doctors care for every patient,\u201d Kauffman added. \u201cOur probabilistic approach helps bridge that gap, making it easier for clinicians to see which research findings truly apply to the patient in front of them.\u201d\u00a0\u00a0<\/p>\n\n\n\n<div style=\"height:18px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p><strong>Source:<\/strong> <a href=\"https:\/\/www.mountsinai.org\/about\/newsroom\/2025\/ai-system-finds-crucial-clues-for-diagnoses-in-electronic-health-records\" target=\"_blank\" rel=\"noopener\" title=\"\">Icahn School of Medicine at Mount Sinai<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>A breakthrough in artificial intelligence could soon revolutionize how doctors diagnose diseases. Researchers at the Icahn School of Medicine at Mount Sinai and their collaborators have developed InfEHR, an AI system that connects disparate medical events over time. This innovative technology is capable of revealing hidden patterns within electronic health records (EHRs), transforming millions of [&hellip;]<\/p>\n","protected":false},"author":3,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"single-no-separators","format":"standard","meta":{"_acf_changed":false,"_uag_custom_page_level_css":"","_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[8,12],"tags":[172],"class_list":["post-30616","post","type-post","status-publish","format-standard","hentry","category-ai","category-health","tag-icahn-school-of-medicine-at-mount-sinai"],"acf":[],"aioseo_notices":[],"uagb_featured_image_src":{"full":false,"thumbnail":false,"medium":false,"medium_large":false,"large":false,"1536x1536":false,"2048x2048":false},"uagb_author_info":{"display_name":"The University Network","author_link":"https:\/\/www.tun.com\/home\/author\/funky_junkie\/"},"uagb_comment_info":0,"uagb_excerpt":"A breakthrough in artificial intelligence could soon revolutionize how doctors diagnose diseases. Researchers at the Icahn School of Medicine at Mount Sinai and their collaborators have developed InfEHR, an AI system that connects disparate medical events over time. This innovative technology is capable of revealing hidden patterns within electronic health records (EHRs), transforming millions of&hellip;","_links":{"self":[{"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/posts\/30616","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/comments?post=30616"}],"version-history":[{"count":8,"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/posts\/30616\/revisions"}],"predecessor-version":[{"id":30641,"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/posts\/30616\/revisions\/30641"}],"wp:attachment":[{"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/media?parent=30616"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/categories?post=30616"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/tags?post=30616"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}