{"id":121373,"date":"2026-02-17T09:08:06","date_gmt":"2026-02-17T09:08:06","guid":{"rendered":"https:\/\/ekamu.net\/?p=121373"},"modified":"2026-02-17T09:08:06","modified_gmt":"2026-02-17T09:08:06","slug":"yapay-zeka-organ-naklinde-erken-risk-tespit-donemini-baslatiyor","status":"publish","type":"post","link":"https:\/\/ekamu.net\/index.php\/2026\/02\/17\/yapay-zeka-organ-naklinde-erken-risk-tespit-donemini-baslatiyor\/","title":{"rendered":"Yapay zeka, organ naklinde erken risk tespit d\u00f6nemini ba\u015flat\u0131yor"},"content":{"rendered":"<p><figure> <span> <img decoding=\"async\" src=\"https:\/\/ekamu.net\/wp-content\/uploads\/2026\/02\/yapay-zeka-organ-naklinde-erken-risk-tespit-donemini-baslatiyor-0-65acCqmI.jpg\"\/> <\/span> <strong>BIOPREVENT <\/strong>adl\u0131 yeni bir yapay zek\u00e2 arac\u0131, k\u00f6k h\u00fccre ve kemik ili\u011fi nakli sonras\u0131 ortaya \u00e7\u0131kabilecek ciddi sa\u011fl\u0131k sorunlar\u0131n\u0131 <strong>belirtiler ba\u015flamadan aylar \u00f6nce<\/strong> tahmin edebiliyor. MUSC Hollings Kanser Merkezi ara\u015ft\u0131rmac\u0131lar\u0131 taraf\u0131ndan geli\u015ftirilen sistemin sonu\u00e7lar\u0131, Journal of Clinical Investigation dergisinde yay\u0131mland\u0131. Ara\u00e7, nakilden yakla\u015f\u0131k 90 ila 100 g\u00fcn sonra toplanan hasta verilerini analiz ederek, ba\u011f\u0131\u015f\u0131kl\u0131k sisteminin yetersiz kalmas\u0131 gibi nedenlerden ortaya \u00e7\u0131kan kronik greft-konak\u00e7\u0131 hastal\u0131\u011f\u0131 ve nakille ba\u011flant\u0131l\u0131 \u00f6l\u00fcm riski hakk\u0131nda erken uyar\u0131 veriyor. Bu sayede doktorlar\u0131n, sorunlar belirginle\u015fmeden \u00f6nce riskli hastalar\u0131 tespit edebilmesi hedefleniyor. <\/figure>\n<p><b>BIOPREVENT isimli yapay zek\u00e2 arac\u0131 organ nakli sonras\u0131 riskleri aylar \u00f6ncesinden g\u00f6r\u00fcyor<\/b><\/p>\n<p>Ara\u015ft\u0131rma ekibi, d\u00f6rt b\u00fcy\u00fck \u00e7al\u0131\u015fmadan elde edilen toplam 1.310 nakil hastas\u0131n\u0131n verilerini inceledi. Kan testlerinde \u00f6l\u00e7\u00fclen baz\u0131 ba\u011f\u0131\u015f\u0131kl\u0131kla ilgili proteinler ile hastalar\u0131n ya\u015f\u0131, nakil t\u00fcr\u00fc ve temel hastal\u0131\u011f\u0131 gibi klinik bilgiler bir araya getirildi. Yapay zek\u00e2 sistemi, bu veriler aras\u0131ndaki ili\u015fkileri analiz ederek hangi hastalar\u0131n ilerleyen d\u00f6nemde daha y\u00fcksek risk ta\u015f\u0131d\u0131\u011f\u0131n\u0131 hesaplad\u0131. G\u00fcnl\u00fck hayatta kredi notu sisteminin ge\u00e7mi\u015f harcama ve \u00f6deme al\u0131\u015fkanl\u0131klar\u0131na bakarak risk analizi yapmas\u0131na benzer \u015fekilde, BIOPREVENT de ge\u00e7mi\u015f ve mevcut sa\u011fl\u0131k verilerinden gelece\u011fe dair bir olas\u0131l\u0131k \u00e7\u0131kar\u0131m\u0131 yap\u0131yor.<\/p>\n<p>Farkl\u0131 yapay zek\u00e2 y\u00f6ntemleri test edildi ve en iyi sonucu veren model, bir y\u0131l i\u00e7inde kronik greft-konak\u00e7\u0131 hastal\u0131\u011f\u0131 geli\u015fme riskini anlaml\u0131 bir do\u011fruluk oran\u0131yla tahmin edebildi. Nakille ba\u011flant\u0131l\u0131 \u00f6l\u00fcm riskinde ise daha da y\u00fcksek do\u011fruluk de\u011ferlerine ula\u015f\u0131ld\u0131. Ara\u015ft\u0131rmac\u0131lar ayr\u0131ca hangi kan de\u011ferlerinin tahmin a\u00e7\u0131s\u0131ndan daha belirleyici oldu\u011funu da ortaya koydu. Bu sayede sistem yaln\u0131zca bir risk var uyar\u0131s\u0131 vermekle kalm\u0131yor, ayn\u0131 zamanda riskin arkas\u0131ndaki biyolojik i\u015faretleri de dikkate al\u0131yor.<\/p>\n<p>BIOPREVENT daha sonra ba\u011f\u0131ms\u0131z bir hasta grubunda da test edilerek do\u011fruland\u0131. Ara\u015ft\u0131rma ekibi, sistemi \u00fccretsiz bir web uygulamas\u0131na d\u00f6n\u00fc\u015ft\u00fcrd\u00fc. Doktorlar bu platforma hasta bilgilerini girerek ki\u015fiye \u00f6zel risk de\u011ferlendirmesi alabiliyor. Ara\u00e7, hastalar\u0131 <strong>18 aya kadar olan s\u00fcre\u00e7te<\/strong> d\u00fc\u015f\u00fck ve y\u00fcksek risk gruplar\u0131na ay\u0131rmada ba\u015far\u0131l\u0131 oldu. Bu ayr\u0131m, \u00f6zellikle hangi hastalar\u0131n daha s\u0131k takip edilmesi gerekti\u011fi konusunda yol g\u00f6sterici olabilir.<\/p>\n<p>\u015eu a\u015famada BIOPREVENT\u2019in do\u011frudan tedavi kararlar\u0131n\u0131 belirlemesi ama\u00e7lanm\u0131yor. Ara\u015ft\u0131rmac\u0131lar, erken risk uyar\u0131lar\u0131na g\u00f6re hareket etmenin hasta sonu\u00e7lar\u0131n\u0131 ger\u00e7ekten iyile\u015ftirip iyile\u015ftirmedi\u011finin klinik \u00e7al\u0131\u015fmalarla netle\u015ftirilmesi gerekti\u011fini vurguluyor. Yani sistem bir karar verici de\u011fil, doktorlara ek bir bilgi katman\u0131 sunan dijital bir destek arac\u0131 olarak konumlan\u0131yor.<\/p>\n\n<p><span style=\"display: block; width: 343.125px; color: rgb(55, 58, 60); font-size: 14px; background-color: rgb(255, 249, 236);\"><\/span><\/p>\n<p>Kaynak :\u00a0<span style=\"background-color: rgb(255, 249, 236); color: rgb(55, 58, 60); font-size: 14px;\">https:\/\/www.donanimhaber.com\/yapay-zeka-organ-naklinde-erken-risk-tespit-donemini-baslatiyor&#8211;202182<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>BIOPREVENT adl\u0131 yeni bir yapay zek\u00e2 arac\u0131, k\u00f6k h\u00fccre ve kemik ili\u011fi nakli sonras\u0131 ortaya \u00e7\u0131kabilecek ciddi sa\u011fl\u0131k sorunlar\u0131n\u0131 belirtiler ba\u015flamadan aylar \u00f6nce tahmin edebiliyor. MUSC Hollings Kanser Merkezi ara\u015ft\u0131rmac\u0131lar\u0131 taraf\u0131ndan geli\u015ftirilen &#8230;<\/p>\n","protected":false},"author":1,"featured_media":121374,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[8],"tags":[314,99,5608,541,641],"class_list":["post-121373","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-teknoloji","tag-arastirma","tag-hasta","tag-nakil","tag-risk","tag-sistem"],"_links":{"self":[{"href":"https:\/\/ekamu.net\/index.php\/wp-json\/wp\/v2\/posts\/121373","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/ekamu.net\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/ekamu.net\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/ekamu.net\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/ekamu.net\/index.php\/wp-json\/wp\/v2\/comments?post=121373"}],"version-history":[{"count":1,"href":"https:\/\/ekamu.net\/index.php\/wp-json\/wp\/v2\/posts\/121373\/revisions"}],"predecessor-version":[{"id":121376,"href":"https:\/\/ekamu.net\/index.php\/wp-json\/wp\/v2\/posts\/121373\/revisions\/121376"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/ekamu.net\/index.php\/wp-json\/wp\/v2\/media\/121374"}],"wp:attachment":[{"href":"https:\/\/ekamu.net\/index.php\/wp-json\/wp\/v2\/media?parent=121373"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/ekamu.net\/index.php\/wp-json\/wp\/v2\/categories?post=121373"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/ekamu.net\/index.php\/wp-json\/wp\/v2\/tags?post=121373"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}