{"id":214395,"date":"2026-04-02T11:11:28","date_gmt":"2026-04-02T08:11:28","guid":{"rendered":"https:\/\/golossokal.com.ua\/?p=214395"},"modified":"2026-04-02T00:16:13","modified_gmt":"2026-04-01T21:16:13","slug":"dyrektor-naybilshoi-likarni-ssha-hotovyy-zaminyty-renthenolohiv-shtuchnym-intelektom","status":"publish","type":"post","link":"https:\/\/golossokal.com.ua\/en\/zdorovia\/dyrektor-naybilshoi-likarni-ssha-hotovyy-zaminyty-renthenolohiv-shtuchnym-intelektom.html","title":{"rendered":"The Director of the Largest Hospital in the United States Is Ready to Replace Radiologists with Artificial Intelligence"},"content":{"rendered":"<p><\/p>\n<div>\n<div class=\"standard-markdown grid-cols-1 grid [&amp;_&gt;_*]:min-w-0 gap-3 standard-markdown\">\n<p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\">One of the most influential healthcare executives in the United States has publicly declared readiness to do what until recently sounded like science fiction \u2014 hand over the initial reading of medical images to <a class=\"underline underline underline-offset-2 decoration-1 decoration-current\/40 hover:decoration-current focus:decoration-current\" href=\"https:\/\/uk.wikipedia.org\/wiki\/%D0%A8%D1%82%D1%83%D1%87%D0%BD%D0%B8%D0%B9_%D1%96%D0%BD%D1%82%D0%B5%D0%BB%D0%B5%D0%BA%D1%82\">artificial intelligence<\/a>, removing radiologists from the front line of diagnosis. As <a class=\"underline underline underline-offset-2 decoration-1 decoration-current\/40 hover:decoration-current focus:decoration-current\" href=\"https:\/\/radiologybusiness.com\/topics\/artificial-intelligence\/ceo-americas-largest-public-hospital-system-says-hes-ready-replace-radiologists-ai\">Radiology Business reports<\/a>, Mitchell Katz, president and CEO of NYC Health + Hospitals \u2014 America\u2019s largest public hospital network \u2014 says the technology is already ready, and the main obstacle is not medical but regulatory. The top executive\u2019s remarks stirred the medical community and ignited a debate that reaches far beyond New York.<\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\"><strong>What is known in brief<\/strong><\/p>\n<ul class=\"[li_&amp;]:mb-0 [li_&amp;]:mt-1 [li_&amp;]:gap-1 [&amp;:not(:last-child)_ul]:pb-1 [&amp;:not(:last-child)_ol]:pb-1 list-disc flex flex-col gap-1 pl-8 mb-3\">\n<li class=\"whitespace-normal break-words pl-2\">Mitchell Katz leads a network of 11 hospitals that serves more than a million New Yorkers annually and has invested $224 million in upgrading GE imaging equipment.<\/li>\n<li class=\"whitespace-normal break-words pl-2\">At a Crain&#8217;s New York Business panel discussion on March 25, 2026, he said: \u201cWe could already replace a significant number of radiologists with AI if we were ready for the regulatory challenge.\u201d<\/li>\n<li class=\"whitespace-normal break-words pl-2\">Fellow panelist David Lubarsky of Westchester Medical Center reported that their AI makes errors in breast cancer diagnosis only <strong>3 times out of 10,000<\/strong> images for low-risk patients \u2014 and that this is \u201cbetter than a human.\u201d<\/li>\n<li class=\"whitespace-normal break-words pl-2\">Radiologists sharply reject this position, calling it \u201cnaive\u201d and dangerous for patients.<\/li>\n<li class=\"whitespace-normal break-words pl-2\">Current New York State law requires mandatory radiologist oversight of any reading of medical images; Katz wants to change that.<\/li>\n<\/ul>\n<h2 class=\"text-text-100 mt-3 -mb-1 text-[1.125rem] font-bold\">What radiology is and why it is a target for AI<\/h2>\n<p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\"><a class=\"underline underline underline-offset-2 decoration-1 decoration-current\/40 hover:decoration-current focus:decoration-current\" href=\"https:\/\/uk.wikipedia.org\/wiki\/%D0%A0%D0%B0%D0%B4%D1%96%D0%BE%D0%BB%D0%BE%D0%B3%D1%96%D1%8F\">Radiology<\/a> is a medical specialty focused on interpreting medical images: X-rays, CT scans, MRIs, <a class=\"underline underline underline-offset-2 decoration-1 decoration-current\/40 hover:decoration-current focus:decoration-current\" href=\"https:\/\/uk.wikipedia.org\/wiki\/%D0%9C%D0%B0%D0%BC%D0%BE%D0%B3%D1%80%D0%B0%D1%84%D1%96%D1%8F\">mammography<\/a>, and ultrasound. A radiologist analyzes these images and reports to the physician findings that may indicate disease. It is one of the most \u201cdigital\u201d specialties in medicine: almost all the work consists of analyzing pixels rather than direct contact with the patient.<\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\">That is why radiology has long been the primary target for medical AI developers. Computer vision is trained to recognize pathological patterns in millions of images and compare them with new ones. In routine screenings, where most images are normal, this task is fundamentally similar to pattern recognition \u2014 and here algorithms really can be highly accurate. <a class=\"underline underline underline-offset-2 decoration-1 decoration-current\/40 hover:decoration-current focus:decoration-current\" href=\"https:\/\/cikavosti.com\/vplyv-shtuchnogo-intelektu-na-krytychne-myslennya\/\">Microsoft research confirms<\/a>: the more a person trusts AI in routine tasks, the less they engage their own critical thinking \u2014 and this principle applies not only to ordinary users, but also to doctors.<\/p>\n<h2 class=\"text-text-100 mt-3 -mb-1 text-[1.125rem] font-bold\">Details of the statement and arguments in favor of AI<\/h2>\n<p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\">Katz came to the discussion with statistics and a concrete proposal. His hospital system has already invested <strong>$224 million<\/strong> in new imaging equipment. Now he wants AI to serve as the \u201cfirst reader\u201d of routine screenings \u2014 primarily mammograms and X-rays \u2014 and only if abnormalities are detected would the image be passed on to a radiologist.<\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\">David Lubarsky, president and CEO of Westchester Medical Center Health Network, backed him up with specific data. Their AI has already been deployed in real practice, and for low-risk women with a negative mammogram result, the system makes errors only three times per ten thousand images. <em>\u201cAI is actually better than humans,\u201d<\/em> he said without reservation. Sandra Scott, director of One Brooklyn Health \u2014 a small hospital with severe financial constraints \u2014 called such an approach \u201crevolutionary\u201d for institutions serving the city\u2019s poorest neighborhoods.<\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\">The logic is simple: <strong>fewer radiologist salaries means broader screening coverage<\/strong> for the same money. Katz directly asked his fellow executives whether there were any reasons not to lobby for changes to New York law to allow AI to read images without mandatory radiologist oversight.<\/p>\n<h2 class=\"text-text-100 mt-3 -mb-1 text-[1.125rem] font-bold\">What real clinical practice shows<\/h2>\n<p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\">A similar discussion had already taken place in the public sphere: Anthropic CEO Dario Amodei recently said on a podcast that AI had already taken over the main function of radiologists. Radiologists criticized those words as an exaggeration. They reacted similarly to Katz\u2019s remarks.<\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\">Mohammed Suhail, a radiologist at North Coast Imaging in San Diego, responded with visible irritation: <em>\u201cIrrefutable proof that arrogantly ignorant hospital administrators are dangerous to patients: they are easily fooled by IT companies that are nowhere close to delivering medical care.\u201d<\/em> According to him, any attempt to implement AI-only image reading <em>\u201cwill immediately lead to patient harm and deaths.\u201d<\/em><\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\">Critics point to a key problem that is <a class=\"underline underline underline-offset-2 decoration-1 decoration-current\/40 hover:decoration-current focus:decoration-current\" href=\"https:\/\/cikavosti.com\/najbilshyj-ryzyk-shtuchnogo-intelektu-u-vyshhij-osviti-polyagaye-ne-v-obmani-a-v-rujnuvanni-samogo-navchannya\/\">well illustrated by the debate about AI in higher education<\/a>: when AI says \u201cnormal\u201d and no radiologist checks it, false negatives become systematically invisible. No one knows what was missed because there is no error-tracking mechanism. Accuracy of 99.97% on curated datasets from academic centers may differ significantly from real-world conditions: different equipment, atypical patients, rare pathologies that were not present in the training data.<\/p>\n<h2 class=\"text-text-100 mt-3 -mb-1 text-[1.125rem] font-bold\">Why this matters for the future of medicine<\/h2>\n<p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\">This controversy is unfolding against the backdrop of a real crisis in radiology: demand for imaging is growing, there are not enough radiologists, and their salaries are rising rapidly. A report by the Neiman Health Policy Institute, published in the journal <a class=\"underline underline underline-offset-2 decoration-1 decoration-current\/40 hover:decoration-current focus:decoration-current\" href=\"https:\/\/www.jacr.org\/\">JACR<\/a>, states: \u201cthese trends most likely indicate that radiology workforce capacity has been exhausted.\u201d One radiologist can physically review only a limited number of images per day.<\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\">At the same time, scientists from Stanford and leading European universities insist that a radiologist\u2019s job is not limited to image classification. It includes triaging complex cases, training residents, and interacting with clinicians in nonstandard situations \u2014 and none of these aspects can yet be automated. Nvidia CEO Jensen Huang recently acknowledged that alarmist predictions about the disappearance of radiologists due to computer vision \u201cwent too far\u201d and negatively affected the influx of young doctors into the specialty.<\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\">There is also a fundamental question of fairness: <a class=\"underline underline underline-offset-2 decoration-1 decoration-current\/40 hover:decoration-current focus:decoration-current\" href=\"https:\/\/cikavosti.com\/rak-u-millenialiv-zrostaye-vcheni-shukayut-prychyny\/\">breast cancer among women is becoming an increasingly widespread problem<\/a>, and if AI-based image reading makes it possible to reach millions of women who currently lack access to screening, the potential benefit could be enormous. But if the percentage of missed cancers rises at the same time, the harm will also be enormous \u2014 and invisible.<\/p>\n<h2 class=\"text-text-100 mt-3 -mb-1 text-[1.125rem] font-bold\">Interesting facts<\/h2>\n<ol class=\"[li_&amp;]:mb-0 [li_&amp;]:mt-1 [li_&amp;]:gap-1 [&amp;:not(:last-child)_ul]:pb-1 [&amp;:not(:last-child)_ol]:pb-1 list-decimal flex flex-col gap-1 pl-8 mb-3\">\n<li class=\"whitespace-normal break-words pl-2\">As of 2026, the U.S. <a class=\"underline underline underline-offset-2 decoration-1 decoration-current\/40 hover:decoration-current focus:decoration-current\" href=\"https:\/\/www.fda.gov\/medical-devices\/software-medical-device-samd\/artificial-intelligence-and-machine-learning-aiml-enabled-medical-devices\">FDA has approved more than 950 AI algorithms for medical devices<\/a>, the overwhelming majority of which relate specifically to radiological diagnostics \u2014 X-rays, CT scans, and MRIs.<\/li>\n<li class=\"whitespace-normal break-words pl-2\">The first AI algorithm for mammogram screening received FDA approval back in 1998. For more than a quarter of a century, this technology was used exclusively as an assistive tool rather than a replacement for a radiologist \u2014 and only now has the debate reached the question of full autonomy. A detailed chronology is provided by the <a class=\"underline underline underline-offset-2 decoration-1 decoration-current\/40 hover:decoration-current focus:decoration-current\" href=\"https:\/\/www.acr.org\/\">American College of Radiology (ACR)<\/a>.<\/li>\n<li class=\"whitespace-normal break-words pl-2\">A missed breast cancer on a mammogram is one of the most common causes of medical lawsuits in the United States. According to <a class=\"underline underline underline-offset-2 decoration-1 decoration-current\/40 hover:decoration-current focus:decoration-current\" href=\"https:\/\/www.nejm.org\/\">The New England Journal of Medicine<\/a>, up to 30% of breast cancer cases are missed on the initial screening read even by experienced radiologists \u2014 which is the main argument of AI supporters.<\/li>\n<li class=\"whitespace-normal break-words pl-2\">The model \u201cAI reads first, radiologist checks the abnormal cases\u201d has already been successfully implemented in Sweden: a study published in <a class=\"underline underline underline-offset-2 decoration-1 decoration-current\/40 hover:decoration-current focus:decoration-current\" href=\"https:\/\/www.thelancet.com\/journals\/lanonc\/home\">The Lancet Oncology<\/a> showed that this approach detects 20% more cancers than standard double reading by two radiologists, while cutting staff workload in half.<\/li>\n<\/ol>\n<h2 class=\"text-text-100 mt-3 -mb-1 text-[1.125rem] font-bold\">FAQ<\/h2>\n<p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\"><strong>Can AI really replace a radiologist?<\/strong> For very narrow and standardized tasks \u2014 for example, the initial screening of mammograms in low-risk women \u2014 the accuracy of modern algorithms is indeed comparable to or exceeds human performance under controlled conditions. But radiology includes hundreds of different types of pathology in complex clinical contexts, where AI still falls far short of an experienced specialist.<\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\"><strong>What exactly is preventing AI from replacing radiologists right now?<\/strong> The main barrier is regulatory. New York State laws and U.S. federal legislation require medical images to be read by a licensed radiologist. Changing this rule would require either a regulator\u2019s decision or new legislative initiatives, as well as, clearly, overcoming resistance from the medical community.<\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\"><strong>What might a compromise option look like?<\/strong> Most experts, including critics of full replacement, agree that AI as a \u201cfirst reader,\u201d followed by radiologist review only of abnormal images, is a promising model. It expands screening coverage, reduces the burden on specialists, and preserves human oversight where it matters most.<\/p>\n<hr class=\"border-border-200 border-t-0.5 my-3 mx-1.5\" \/>\n<p class=\"font-claude-response-body break-words whitespace-normal leading-[1.7]\"><strong>WOW fact:<\/strong> If AI reads mammograms with 99.97% accuracy \u2014 and NYC Health + Hospitals performs hundreds of thousands of them annually \u2014 even those three errors per ten thousand images mean potentially <strong>dozens of missed cancer diagnoses every year<\/strong> in just one hospital network. It is this math, rather than the technology itself, that is the real heart of the controversy.<\/p>\n<\/div>\n<\/div>\n<p><\/p>","protected":false},"excerpt":{"rendered":"<p>One of the most influential healthcare executives in the United States has publicly declared readiness to do what until recently sounded like science fiction \u2014 hand over the initial reading of medical images to artificial intelligence, removing radiologists from the front line of diagnosis. As Radiology Business reports, Mitchell Katz, president and CEO of NYC &hellip;<\/p>\n","protected":false},"author":1,"featured_media":178545,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[190],"tags":[],"class_list":["post-214395","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-zdorovia"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.4 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>The Director of the Largest Hospital in the United States Is Ready to Replace Radiologists with Artificial Intelligence - Sokal Voice - news about Sokal, Sheptytskyi<\/title>\n<meta name=\"description\" content=\"\u0414\u0438\u0440\u0435\u043a\u0442\u043e\u0440 \u043d\u0430\u0439\u0431\u0456\u043b\u044c\u0448\u043e\u0457 \u043f\u0443\u0431\u043b\u0456\u0447\u043d\u043e\u0457 \u043b\u0456\u043a\u0430\u0440\u043d\u0456 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