{"id":207,"date":"2025-06-20T10:25:56","date_gmt":"2025-06-20T17:25:56","guid":{"rendered":"https:\/\/scienceblog.com\/neuroedge\/?p=207"},"modified":"2025-06-20T10:25:56","modified_gmt":"2025-06-20T17:25:56","slug":"human-ai-teams-make-better-medical-diagnoses","status":"publish","type":"post","link":"https:\/\/scienceblog.com\/neuroedge\/2025\/06\/20\/human-ai-teams-make-better-medical-diagnoses\/","title":{"rendered":"Human-AI Teams Make Better Medical Diagnoses"},"content":{"rendered":"<p>Hybrid collectives consisting of humans and artificial intelligence make significantly more accurate medical diagnoses than either medical professionals or AI systems alone. New research analyzing over 40,000 diagnoses reveals that combining human expertise with AI models creates a powerful diagnostic partnership that outperforms traditional approaches.<\/p>\n<p>The study, <a href=\"https:\/\/www.pnas.org\/doi\/10.1073\/pnas.2426153122\">published in Proceedings of the National Academy of Science<\/a>s, examined how physicians and five leading AI language models diagnosed more than 2,100 clinical cases. When working together, these human-AI teams achieved diagnostic accuracy that surpassed both individual doctors and AI-only systems.<\/p>\n<h2>Complementary Strengths and Weaknesses<\/h2>\n<p>The key to success lies in error complementarity\u2014humans and AI make systematically different mistakes. When AI models failed to identify the correct diagnosis, human physicians often provided the right answer, and vice versa.<\/p>\n<p>&#8220;Our results show that cooperation between humans and AI models has great potential to improve patient safety,&#8221; explains lead author Nikolas Z\u00f6ller, a postdoctoral researcher at the Max Planck Institute for Human Development.<\/p>\n<p>The research team found that AI collectives outperformed 85% of individual human diagnosticians. However, in numerous cases where AI failed completely, humans knew the correct diagnosis, often ranking it first in their differential diagnosis lists.<\/p>\n<h2>Dramatic Performance Improvements<\/h2>\n<p>Adding just one AI model to a group of human diagnosticians\u2014or adding one human to AI systems\u2014substantially improved results across multiple metrics:<\/p>\n<ul>\n<li>Top-5 accuracy increased when combining the best AI models with physician groups<\/li>\n<li>Even the worst-performing AI model improved human diagnostic teams<\/li>\n<li>Multiple AI models working together generally outperformed individual systems<\/li>\n<li>Hybrid teams showed the most reliable outcomes across all medical specialties tested<\/li>\n<\/ul>\n<h2>Real-World Clinical Potential<\/h2>\n<p>The researchers used clinical vignettes from the Human Diagnosis Project, which provides realistic case descriptions similar to what physicians encounter in practice. Each case included patient symptoms, medical records, and test results, creating authentic diagnostic challenges.<\/p>\n<p>&#8220;It&#8217;s not about replacing humans with machines. Rather, we should view artificial intelligence as a complementary tool that unfolds its full potential in collective decision-making,&#8221; notes co-author Stefan Herzog, Senior Research Scientist at the Max Planck Institute for Human Development.<\/p>\n<p>The study employed sophisticated text-processing techniques to standardize diagnoses using SNOMED CT medical terminology, allowing precise comparison between human and AI responses. This methodology enabled researchers to analyze diagnosis accuracy across different ranking positions and medical specialties.<\/p>\n<h2>Error Patterns Reveal Opportunities<\/h2>\n<p>When AI systems missed correct diagnoses entirely\u2014occurring in 34% to 54% of cases depending on the model\u2014individual humans provided the right answer 30% to 38% of the time. Conversely, when humans failed completely, AI models compensated in 31% to 51% of cases.<\/p>\n<p>The research revealed that humans and AI disagree on their top diagnosis choice in substantial numbers of cases, but this disagreement proves beneficial rather than problematic. The error diversity ensures correct diagnoses accumulate more frequently than incorrect ones in collective decision-making.<\/p>\n<h2>Broader Applications and Limitations<\/h2>\n<p>Study coordinator Vito Trianni sees applications beyond medicine: &#8220;The approach can also be transferred to other critical areas\u2014such as the legal system, disaster response, or climate policy\u2014anywhere that complex, high-risk decisions are needed.&#8221;<\/p>\n<p>However, researchers acknowledge important limitations. The study analyzed text-based case vignettes rather than actual patients in clinical settings. Whether results translate directly to real medical practice requires further investigation.<\/p>\n<p>The research also focused solely on diagnosis, not treatment decisions. A correct diagnosis doesn&#8217;t automatically guarantee optimal patient care, and the study didn&#8217;t examine how AI-based support systems would be accepted by medical staff and patients.<\/p>\n<h2>Future Implications<\/h2>\n<p>The findings highlight particular promise for regions with limited healthcare access, where hybrid human-AI systems could contribute to more equitable medical care. The approach might help bridge gaps in medical expertise while maintaining essential human oversight.<\/p>\n<p>As diagnostic errors cause an estimated 795,000 deaths and permanent disabilities in the United States annually, these results suggest significant potential for improving patient safety through thoughtful human-AI collaboration rather than wholesale replacement of human judgment.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Hybrid collectives consisting of humans and artificial intelligence make significantly more accurate medical diagnoses than either medical professionals or AI systems alone. New research analyzing over 40,000 diagnoses reveals that combining human expertise with AI models creates a powerful diagnostic partnership that outperforms traditional approaches. The study, published in Proceedings of the National Academy of &#8230; <a title=\"Human-AI Teams Make Better Medical Diagnoses\" class=\"read-more\" href=\"https:\/\/scienceblog.com\/neuroedge\/2025\/06\/20\/human-ai-teams-make-better-medical-diagnoses\/\" aria-label=\"Read more about Human-AI Teams Make Better Medical Diagnoses\">Read more<\/a><\/p>\n","protected":false},"author":1297,"featured_media":208,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[2,4,6],"tags":[],"class_list":["post-207","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-automation-efficiency","category-computational-innovation","category-technology","generate-columns","tablet-grid-50","mobile-grid-100","grid-parent","grid-50"],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v27.4 (Yoast SEO v27.4) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>Human-AI Teams Make Better Medical Diagnoses - NeuroEdge<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/scienceblog.com\/neuroedge\/2025\/06\/20\/human-ai-teams-make-better-medical-diagnoses\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Human-AI Teams Make Better Medical Diagnoses\" \/>\n<meta property=\"og:description\" content=\"Hybrid collectives consisting of humans and artificial intelligence make significantly more accurate medical diagnoses than either medical professionals or AI systems alone. New research analyzing over 40,000 diagnoses reveals that combining human expertise with AI models creates a powerful diagnostic partnership that outperforms traditional approaches. The study, published in Proceedings of the National Academy of ... 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Researchers at the Icahn School of Medicine at Mount Sinai have now developed an artificial intelligence system that transforms this flood of information into structured insight. The tool, called InfEHR,\u2026","rel":"","context":"In &quot;Automation &amp; Efficiency&quot;","block_context":{"text":"Automation &amp; Efficiency","link":"https:\/\/scienceblog.com\/neuroedge\/category\/automation-efficiency\/"},"img":{"alt_text":"clinician carrying a health record","src":"https:\/\/i0.wp.com\/scienceblog.com\/neuroedge\/wp-content\/uploads\/sites\/14\/2025\/10\/pexels-karolina-grabowska-6627823.jpg?resize=350%2C200&ssl=1","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/scienceblog.com\/neuroedge\/wp-content\/uploads\/sites\/14\/2025\/10\/pexels-karolina-grabowska-6627823.jpg?resize=350%2C200&ssl=1 1x, https:\/\/i0.wp.com\/scienceblog.com\/neuroedge\/wp-content\/uploads\/sites\/14\/2025\/10\/pexels-karolina-grabowska-6627823.jpg?resize=525%2C300&ssl=1 1.5x, https:\/\/i0.wp.com\/scienceblog.com\/neuroedge\/wp-content\/uploads\/sites\/14\/2025\/10\/pexels-karolina-grabowska-6627823.jpg?resize=700%2C400&ssl=1 2x"},"classes":[]},{"id":31,"url":"https:\/\/scienceblog.com\/neuroedge\/2025\/04\/18\/ai-matches-non-specialists-in-medical-diagnosis\/","url_meta":{"origin":207,"position":1},"title":"AI Matches Non-Specialists In Medical Diagnosis","author":"NeuroEdge","date":"April 18, 2025","format":false,"excerpt":"The latest AI systems are now diagnosing medical conditions about as well as junior doctors, according to a sweeping new analysis that's likely to raise eyebrows across healthcare. While seasoned specialists still outperform the machines, this milestone suggests we're entering a new era where AI could meaningfully augment medical education\u2026","rel":"","context":"In &quot;Automation &amp; Efficiency&quot;","block_context":{"text":"Automation &amp; Efficiency","link":"https:\/\/scienceblog.com\/neuroedge\/category\/automation-efficiency\/"},"img":{"alt_text":"Clinician at monitoring equipment","src":"https:\/\/i0.wp.com\/scienceblog.com\/neuroedge\/wp-content\/uploads\/sites\/14\/2025\/04\/medical-equipment-4099428_1280.jpg?resize=350%2C200&ssl=1","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/scienceblog.com\/neuroedge\/wp-content\/uploads\/sites\/14\/2025\/04\/medical-equipment-4099428_1280.jpg?resize=350%2C200&ssl=1 1x, https:\/\/i0.wp.com\/scienceblog.com\/neuroedge\/wp-content\/uploads\/sites\/14\/2025\/04\/medical-equipment-4099428_1280.jpg?resize=525%2C300&ssl=1 1.5x, https:\/\/i0.wp.com\/scienceblog.com\/neuroedge\/wp-content\/uploads\/sites\/14\/2025\/04\/medical-equipment-4099428_1280.jpg?resize=700%2C400&ssl=1 2x, https:\/\/i0.wp.com\/scienceblog.com\/neuroedge\/wp-content\/uploads\/sites\/14\/2025\/04\/medical-equipment-4099428_1280.jpg?resize=1050%2C600&ssl=1 3x"},"classes":[]},{"id":245,"url":"https:\/\/scienceblog.com\/neuroedge\/2025\/09\/29\/ai-distinguishes-glioblastoma-from-look-alike-cancers-during-surgery\/","url_meta":{"origin":207,"position":2},"title":"AI Distinguishes Glioblastoma From Look-Alike Cancers During Surgery","author":"NeuroEdge","date":"September 29, 2025","format":false,"excerpt":"In the high-stakes world of brain surgery, a pathologist's snap judgment can determine whether a patient walks out with their tumor removed or heads straight to chemotherapy instead. Get it wrong, and you've either carved out healthy brain tissue unnecessarily or left dangerous cells behind. Now, an AI system called\u2026","rel":"","context":"In &quot;Brain Health&quot;","block_context":{"text":"Brain Health","link":"https:\/\/scienceblog.com\/neuroedge\/category\/brain-health\/"},"img":{"alt_text":"glioblastoma tumor imaging","src":"https:\/\/i0.wp.com\/scienceblog.com\/neuroedge\/wp-content\/uploads\/sites\/14\/2025\/09\/Researchers-make-glioblastoma-cells-visible-to-attacking-immune-cells-600x400-1.webp?resize=350%2C200&ssl=1","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/scienceblog.com\/neuroedge\/wp-content\/uploads\/sites\/14\/2025\/09\/Researchers-make-glioblastoma-cells-visible-to-attacking-immune-cells-600x400-1.webp?resize=350%2C200&ssl=1 1x, https:\/\/i0.wp.com\/scienceblog.com\/neuroedge\/wp-content\/uploads\/sites\/14\/2025\/09\/Researchers-make-glioblastoma-cells-visible-to-attacking-immune-cells-600x400-1.webp?resize=525%2C300&ssl=1 1.5x"},"classes":[]},{"id":240,"url":"https:\/\/scienceblog.com\/neuroedge\/2025\/08\/06\/ai-chatbots-often-spread-medical-falsehoods-study-finds\/","url_meta":{"origin":207,"position":3},"title":"AI Chatbots Often Spread Medical Falsehoods, Study Finds","author":"NeuroEdge","date":"August 6, 2025","format":false,"excerpt":"Artificial intelligence chatbots like ChatGPT are being widely used in healthcare, but a new study warns they may be dangerously susceptible to medical misinformation. Researchers at the Icahn School of Medicine at Mount Sinai found that leading AI models often repeat or even elaborate on false clinical details embedded in\u2026","rel":"","context":"In &quot;Automation &amp; Efficiency&quot;","block_context":{"text":"Automation &amp; Efficiency","link":"https:\/\/scienceblog.com\/neuroedge\/category\/automation-efficiency\/"},"img":{"alt_text":"clownish looking ai chatbots at a call center","src":"https:\/\/i0.wp.com\/scienceblog.com\/neuroedge\/wp-content\/uploads\/sites\/14\/2025\/08\/ai-generated-7783344_1280.jpg?resize=350%2C200&ssl=1","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/scienceblog.com\/neuroedge\/wp-content\/uploads\/sites\/14\/2025\/08\/ai-generated-7783344_1280.jpg?resize=350%2C200&ssl=1 1x, https:\/\/i0.wp.com\/scienceblog.com\/neuroedge\/wp-content\/uploads\/sites\/14\/2025\/08\/ai-generated-7783344_1280.jpg?resize=525%2C300&ssl=1 1.5x, https:\/\/i0.wp.com\/scienceblog.com\/neuroedge\/wp-content\/uploads\/sites\/14\/2025\/08\/ai-generated-7783344_1280.jpg?resize=700%2C400&ssl=1 2x"},"classes":[]},{"id":73,"url":"https:\/\/scienceblog.com\/neuroedge\/2025\/04\/24\/ai-fails-to-read-human-social-cues\/","url_meta":{"origin":207,"position":4},"title":"AI Fails To Read Human Social Cues","author":"NeuroEdge","date":"April 24, 2025","format":false,"excerpt":"Despite rapid advances in artificial intelligence, humans still maintain a significant edge when it comes to understanding social interactions, according to new research from Johns Hopkins University that reveals fundamental limitations in AI's ability to interpret human behavior. The study, presented at the International Conference on Learning Representations, found that\u2026","rel":"","context":"In &quot;Computational Innovation&quot;","block_context":{"text":"Computational Innovation","link":"https:\/\/scienceblog.com\/neuroedge\/category\/computational-innovation\/"},"img":{"alt_text":"A man covering his eyes in embarassment","src":"https:\/\/i0.wp.com\/scienceblog.com\/neuroedge\/wp-content\/uploads\/sites\/14\/2025\/04\/man-379800_1280.jpg?resize=350%2C200&ssl=1","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/scienceblog.com\/neuroedge\/wp-content\/uploads\/sites\/14\/2025\/04\/man-379800_1280.jpg?resize=350%2C200&ssl=1 1x, https:\/\/i0.wp.com\/scienceblog.com\/neuroedge\/wp-content\/uploads\/sites\/14\/2025\/04\/man-379800_1280.jpg?resize=525%2C300&ssl=1 1.5x, https:\/\/i0.wp.com\/scienceblog.com\/neuroedge\/wp-content\/uploads\/sites\/14\/2025\/04\/man-379800_1280.jpg?resize=700%2C400&ssl=1 2x"},"classes":[]},{"id":263,"url":"https:\/\/scienceblog.com\/neuroedge\/2025\/11\/19\/he-taught-ai-to-say-i-dont-know\/","url_meta":{"origin":207,"position":5},"title":"He Taught AI to Say &#8220;I Don&#8217;t Know&#8221;","author":"NeuroEdge","date":"November 19, 2025","format":false,"excerpt":"Artificial intelligence can diagnose disease, write essays, and generate art. But it often refuses to admit when it's wrong. Now, a University of Arizona astronomer has found a way to change that. In a preprint posted to arXiv, Peter Behroozi introduces a new method for reducing hallucinations in large-scale AI\u2026","rel":"","context":"In &quot;Computational Innovation&quot;","block_context":{"text":"Computational Innovation","link":"https:\/\/scienceblog.com\/neuroedge\/category\/computational-innovation\/"},"img":{"alt_text":"Light rays are propagating smoothly through a noisy, high-dimensional space in this artist\u2019s impression. 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