Sa\u011fl\u0131k hizmetlerinde AI, daha verimli bilgisayar g\u00f6r\u00fc\u015f\u00fc tabanl\u0131 makine \u00f6\u011frenimi modellerinin geli\u015ftirilmesiyle daha yayg\u0131nd\u0131r.<\/p>\n
Makine \u00f6\u011frenimi algoritmas\u0131 ile daha fazla e\u011fitim verisi kullan\u0131lacak. Bu, yapay zeka modelinin daha fazla de\u011fi\u015fken \u00f6\u011frenmesine olanak sa\u011flayacak ve sa\u011fl\u0131k profesyonellerinin sonu\u00e7lar\u0131 daha do\u011fru bir \u015fekilde tahmin etmesini kolayla\u015ft\u0131racakt\u0131r.<\/p>\n
A\u00e7\u0131klamal\u0131 t\u0131bbi g\u00f6r\u00fcnt\u00fcler, e\u011fitim verilerini daha kullan\u0131\u015fl\u0131 ve verimli hale getirmek i\u00e7in makineler arac\u0131l\u0131\u011f\u0131yla hastal\u0131klar\u0131 veya di\u011fer rahats\u0131zl\u0131klar\u0131 tespit etmek i\u00e7in kullan\u0131labilir. T\u0131bbi g\u00f6r\u00fcnt\u00fclere a\u00e7\u0131klama eklemek, bu t\u00fcr verileri kabul edilebilir bir do\u011frulukla olu\u015fturan bir s\u00fcre\u00e7tir.<\/p>\n
T\u0131bbi g\u00f6r\u00fcnt\u00fclere a\u00e7\u0131klama eklemek, Ultrason, MRI ve BT Taramas\u0131 gibi t\u0131bbi g\u00f6r\u00fcnt\u00fcleme verilerini etiketleme eylemidir. Makine \u00f6\u011frenimi e\u011fitimi.<\/p>\n
Bu radyolog g\u00f6r\u00fcnt\u00fcleri sadece bunlar de\u011fil. Metin bi\u00e7imindeki di\u011fer t\u0131bbi kay\u0131tlar da, derin \u00f6\u011frenme algoritmalar\u0131n\u0131 kullanan makinelerin do\u011fru tahminde bulunmas\u0131 i\u00e7in anla\u015f\u0131l\u0131r olmalar\u0131 amac\u0131yla a\u00e7\u0131klama eklenebilir.<\/p>\n
T\u0131bbi g\u00f6r\u00fcnt\u00fclere a\u00e7\u0131klama eklemek, sa\u011fl\u0131k sekt\u00f6r\u00fcn\u00fcn \u00f6nemli bir par\u00e7as\u0131d\u0131r. \u015eimdi bu ek a\u00e7\u0131klaman\u0131n rol\u00fcn\u00fc ve \u00f6nemini tart\u0131\u015faca\u011f\u0131z. Her bir hastal\u0131k i\u00e7in e\u011fitim veri setleri olu\u015fturmak amac\u0131yla a\u00e7\u0131klama eklenebilecek farkl\u0131 t\u0131bbi g\u00f6r\u00fcnt\u00fc t\u00fcrleri nelerdir?<\/p>\n
T\u0131bbi g\u00f6r\u00fcnt\u00fclere a\u00e7\u0131klama eklemek, AI \u00f6zellikli makineler, cihazlar ve bilgisayarlar kullan\u0131larak \u00e7e\u015fitli hastal\u0131klar\u0131n te\u015fhisinde \u00f6nemli bir bile\u015fendir.<\/p>\n
Bu s\u00fcre\u00e7 asl\u0131nda \u00f6\u011frenme algoritmalar\u0131na veri sa\u011flar. Model daha sonra benzer t\u0131bbi g\u00f6r\u00fcnt\u00fclerdeki hastal\u0131klar\u0131 tespit etmek i\u00e7in kullan\u0131labilir.<\/p>\n
T\u0131bbi g\u00f6r\u00fcnt\u00fc notu, l\u00f6semi gibi kanserli hastal\u0131klardan normal kemik k\u0131r\u0131klar\u0131na kadar \u00e7e\u015fitli hastal\u0131klar\u0131 tespit edebilir.<\/p>\n
Yapay zekan\u0131n t\u0131bbi g\u00f6r\u00fcnt\u00fcleme te\u015fhisinde hangi t\u00fcr te\u015fhis veya hastal\u0131k ger\u00e7ekle\u015ftirdi\u011fi burada g\u00f6r\u00fclebilir. Bu, t\u0131bbi g\u00f6r\u00fcnt\u00fc ek a\u00e7\u0131klamalar\u0131ndan elde edilen verilerin kullan\u0131lmas\u0131yla m\u00fcmk\u00fcn olmu\u015ftur.<\/p>\n
Beyin Bozukluklar\u0131n\u0131 Te\u015fhis Edin<\/strong><\/p>\n A\u00e7\u0131klamal\u0131 t\u0131bbi g\u00f6r\u00fcnt\u00fcler, beyin t\u00fcm\u00f6rleri, kan p\u0131ht\u0131la\u015fmas\u0131 veya di\u011fer n\u00f6rolojik bozukluklar dahil olmak \u00fczere hastal\u0131klar\u0131 te\u015fhis etmek i\u00e7in kullan\u0131l\u0131r. Makine \u00f6\u011frenimi modelleri, a\u00e7\u0131klamal\u0131 g\u00f6r\u00fcnt\u00fclerle iyi e\u011fitilirlerse CT Taramas\u0131 ve MRI kullanarak bu hastal\u0131klar\u0131 tespit edebilir.<\/p>\n N\u00f6ro-g\u00f6r\u00fcnt\u00fclemede yapay zeka, beyin yaralanmalar\u0131 veya di\u011fer ko\u015fullar do\u011fru bir \u015fekilde a\u00e7\u0131kland\u0131\u011f\u0131nda m\u00fcmk\u00fcnd\u00fcr. Bu, do\u011fru tahmini yapmak i\u00e7in makine \u00f6\u011frenimi algoritmas\u0131na beslenir.<\/p>\n Model e\u011fitildikten sonra, daha iyi ve verimli t\u0131bbi g\u00f6r\u00fcnt\u00fc sa\u011flamak i\u00e7in bir radyolog yerine kullan\u0131labilir. Te\u015fhis<\/a> s\u00fcre\u00e7ler. Bu, radyolo\u011fun ba\u015fka kararlar al\u0131rken harcad\u0131\u011f\u0131 zamandan ve \u00e7abadan tasarruf etmesini sa\u011flar.<\/p>\n Karaci\u011fer Sorunlar\u0131n\u0131 Te\u015fhis Edin<\/strong><\/p>\n Karaci\u011fer sorunlar\u0131n\u0131 veya komplikasyonlar\u0131n\u0131 te\u015fhis etmek i\u00e7in ultrason g\u00f6r\u00fcnt\u00fclerini ve di\u011fer t\u0131bbi g\u00f6r\u00fcnt\u00fcleme formatlar\u0131n\u0131 kullanan t\u0131p uzmanlar\u0131 bunlar\u0131 tan\u0131mlayabilir.<\/p>\n Doktorlar genellikle karaci\u011fer t\u0131bbi g\u00f6r\u00fcnt\u00fclerine bakarak hastal\u0131klar\u0131 g\u00f6rsel olarak tespit eder, karakterize eder ve izler. Baz\u0131 durumlarda, ki\u015fisel deneyimi ve yanl\u0131\u015fl\u0131\u011f\u0131, \u00f6nyarg\u0131l\u0131 olmas\u0131na neden olabilir.<\/p>\n T\u0131bbi g\u00f6r\u00fcnt\u00fc ek a\u00e7\u0131klamas\u0131, daha kesin ve tekrarlanabilir g\u00f6r\u00fcnt\u00fcleme te\u015fhisine yol a\u00e7acak niteliksel muhakeme yerine, AI modelini g\u00f6r\u00fcnt\u00fcleme bilgilerini otomatik olarak tan\u0131mas\u0131 i\u00e7in e\u011fitmek i\u00e7in kullan\u0131labilir.<\/p>\n B\u00f6brek Ta\u015flar\u0131 Nas\u0131l Tespit Edilir?<\/strong><\/p>\n Enfeksiyon veya ta\u015f gibi benzer sorunlar b\u00f6brekleri de etkileyebilir.<\/p>\n B\u00f6brek hastal\u0131\u011f\u0131nda AI hen\u00fcz \u00f6nemli olmasa da, \u015fu anda Uyar\u0131 sistemleri ve Te\u015fhis yard\u0131m\u0131, Tedaviye rehberlik etme, Prognozu de\u011ferlendirme ve Tedaviye rehberlik etme gibi temel hususlara odaklanmaktad\u0131r.<\/p>\n Algoritmalar, do\u011fru a\u00e7\u0131klamal\u0131 veri setlerine sahiplerse b\u00f6brek yetmezli\u011fini bile te\u015fhis edebilir.<\/p>\n S\u0131n\u0131rlay\u0131c\u0131 kutu ek a\u00e7\u0131klamas\u0131 d\u0131\u015f\u0131nda, di\u011fer bir\u00e7ok t\u0131bbi g\u00f6r\u00fcnt\u00fc ek a\u00e7\u0131klamas\u0131<\/a> g\u00f6r\u00fcnt\u00fclere a\u00e7\u0131klama eklemek i\u00e7in teknikler kullan\u0131l\u0131r. Bu, farkl\u0131 problemlerle ilgili b\u00f6brekleri tespit etmeyi m\u00fcmk\u00fcn k\u0131lar.<\/p>\n Kanser h\u00fccrelerinin tespiti<\/strong><\/p>\n AI \u00f6zellikli makineler, kanserleri tespit etmeye ve hayat kurtarmaya yard\u0131mc\u0131 oluyor. Kanser erken yakalanmazsa tedavi edilemez hale gelebilir ve iyile\u015fmesi uzun zaman alabilir.<\/p>\n K\u00fcresel olarak, meme kanseri ve prostat kanseri en yayg\u0131n kanserlerden ikisidir. Her ikisi de hem erkeklerde hem de kad\u0131nlarda bulunabilir.<\/p>\n Yapay zeka modelleri art\u0131k, makine \u00f6\u011frenimi modellerinin kanserle ilgili hastal\u0131klar\u0131n durumunu tahmin etmek i\u00e7in bu t\u00fcr verilerden \u00f6\u011frenmesine yard\u0131mc\u0131 olmak i\u00e7in t\u0131bbi g\u00f6r\u00fcnt\u00fc ek a\u00e7\u0131klamalar\u0131yla e\u011fitilebilir.<\/p>\n Di\u015f Analizi i\u00e7in Di\u015f Segmentasyonu<\/strong><\/p>\n AI \u00f6zellikli cihazlar, di\u015f eti veya di\u015f problemlerinin te\u015fhis edilmesine yard\u0131mc\u0131 olabilir. AI, di\u015f yap\u0131s\u0131 da dahil olmak \u00fczere bir\u00e7ok a\u011f\u0131z sorununu tespit edebilir.<\/p>\n Evet, makine \u00f6\u011frenimi algoritmalar\u0131, y\u00fcksek kaliteli e\u011fitim veri k\u00fcmelerinden kal\u0131plar\u0131 tan\u0131yabilir ve bunlar\u0131 ileride ba\u015fvurmak \u00fczere sanal bellekte saklayabilir.<\/p>\n A\u00e7\u0131klamal\u0131 t\u0131bbi g\u00f6r\u00fcnt\u00fcler, Di\u015f Hekimli\u011finde yapay zeka i\u00e7in e\u011fitim verileri olarak kullan\u0131labilir. Model hem nicel hem de nitel verilerden \u00f6\u011frenecektir. Bu, di\u015f g\u00f6r\u00fcnt\u00fclerini analiz etmek i\u00e7in makine \u00f6\u011freniminde daha iyi do\u011fruluk sa\u011flayacakt\u0131r.<\/p>\n G\u00f6z H\u00fccrelerinin Analizi<\/strong><\/p>\n Retina g\u00f6r\u00fcnt\u00fcleri, g\u00f6zleri taramak ve katarakt veya ok\u00fcler hastal\u0131k gibi \u00e7e\u015fitli durumlar\u0131 tespit etmek i\u00e7in kullan\u0131labilir.<\/p>\n Bu semptomlar\u0131n t\u00fcm\u00fc, hastal\u0131\u011f\u0131 te\u015fhis etmek i\u00e7in do\u011fru teknikler kullan\u0131larak tan\u0131mlanabilir.<\/p>\n H\u00fccrelerin Mikroskobik Analizi<\/strong><\/p>\n Mikroskobik h\u00fccrelerin normal insan g\u00f6z\u00fcyle g\u00f6r\u00fclmesi zordur. Ancak mikroskop onlar\u0131 kolayca g\u00f6rmenize yard\u0131mc\u0131 olabilir.<\/p>\n Bu \u00e7ok k\u00fc\u00e7\u00fck h\u00fccrelerin makineler taraf\u0131ndan kolayca tan\u0131nmas\u0131n\u0131 sa\u011flamak i\u00e7in, model geli\u015ftirmede y\u00fcksek kaliteli bir g\u00f6r\u00fcnt\u00fc a\u00e7\u0131klama tekni\u011fi kullan\u0131lmal\u0131d\u0131r.<\/p>\n Mikroskobik h\u00fccrelerin bu g\u00f6r\u00fcnt\u00fcleri, daha b\u00fcy\u00fck bir bilgisayar ekran\u0131nda b\u00fcy\u00fct\u00fclebilir ve geli\u015fmi\u015f ara\u00e7lar ve teknikler kullan\u0131larak a\u00e7\u0131klama eklenebilir.<\/p>\n G\u00f6r\u00fcnt\u00fcler, sa\u011fl\u0131k hizmetlerindeki yapay zekan\u0131n kesin sonu\u00e7lar \u00fcretebilmesini sa\u011flamak i\u00e7in en y\u00fcksek do\u011fruluk d\u00fczeyinde a\u00e7\u0131klamal\u0131d\u0131r. Uzmanlar\u0131m\u0131z, hastal\u0131klar\u0131n tespit edildi\u011fi ve analiz edildi\u011fi mikroskobik h\u00fccreleri etiketleyebilir.<\/p>\n Te\u015fhis G\u00f6r\u00fcnt\u00fcleme Analizi<\/strong><\/p>\n MRI, CT ve CT taramalar\u0131 gibi tan\u0131sal g\u00f6r\u00fcnt\u00fcleme, hastal\u0131\u011f\u0131 g\u00f6rmenin ve en iyi tedaviyi belirlemenin daha iyi bir yoludur.<\/p>\n G\u00f6r\u00fcnt\u00fc a\u00e7\u0131klama ekibinin uzmanlar\u0131, \u00e7e\u015fitli a\u00e7\u0131klama teknikleri kullanarak g\u00f6r\u00fcnt\u00fcleme olu\u015fturabilir ve belirli hastal\u0131klar\u0131 etiketleyebilir.<\/p>\n Radyolojide t\u0131bbi g\u00f6r\u00fcnt\u00fclere a\u00e7\u0131klama eklemek, yapay zekaya radyolojide yeni bir boyut kazand\u0131r\u0131yor. Makine \u00f6\u011frenimi s\u00fcrecine yard\u0131mc\u0131 olacak bir\u00e7ok etiket verisi vard\u0131r.<\/p>\n Denetimli makine \u00f6\u011frenimi i\u00e7in a\u00e7\u0131klamal\u0131 resimler gereklidir.<\/p>\n T\u0131bbi Kay\u0131tlar i\u00e7in Dok\u00fcmantasyon<\/strong><\/p>\n T\u0131bbi g\u00f6r\u00fcnt\u00fc notu, verilerin makine taraf\u0131ndan kolayca tan\u0131nmas\u0131n\u0131 sa\u011flamak i\u00e7in kullan\u0131lan metin dosyalar\u0131n\u0131 da i\u00e7erir. T\u0131bbi kay\u0131tlardaki veriler, hastalar ve sa\u011fl\u0131klar\u0131 hakk\u0131nda bilgi sa\u011flayarak makine \u00f6\u011frenimi modellerini e\u011fitmek i\u00e7in kullan\u0131labilir. T\u0131bbi kay\u0131tlara kesin meta veriler ve metin ek a\u00e7\u0131klamalar\u0131 eklenerek makine \u00f6\u011frenimi geli\u015ftirmesi daha kolay hale getirilebilir. Bu belgeler, y\u00fcksek do\u011fruluk ve gizlilik ile y\u00fcksek vas\u0131fl\u0131 a\u00e7\u0131klay\u0131c\u0131lar taraf\u0131ndan etiketlenebilir.<\/p>\n T\u0131bbi G\u00f6r\u00fcnt\u00fc Ek A\u00e7\u0131klamal\u0131 a\u00e7\u0131klamal\u0131 belge t\u00fcrleri<\/strong><\/p>\n AI t\u0131bbi te\u015fhis \u015firketleri, hassas belgelere kabul edilebilir bir do\u011frulukla a\u00e7\u0131klama eklemek i\u00e7in \u00e7ok fazla veriye ihtiya\u00e7 duyar.<\/p>\n Labelify, en iyi t\u0131bbi g\u00f6r\u00fcnt\u00fc a\u00e7\u0131klama hizmetini sunar. Sa\u011fl\u0131k hizmetlerinde AI i\u00e7in t\u0131bbi g\u00f6r\u00fcnt\u00fclere a\u00e7\u0131klama ekleyebilir. Radyoloji g\u00f6r\u00fcnt\u00fclerini \u00e7ok detayl\u0131 bir \u015fekilde a\u00e7\u0131klayabilir.<\/p>\n Labelify, farkl\u0131 end\u00fcstri ve sekt\u00f6rlerde \u00e7ok say\u0131da AI e\u011fitim veri seti olu\u015fturman\u0131za olanak tan\u0131yan g\u00fc\u00e7l\u00fc bir platformdur.<\/p>\n Sa\u011fl\u0131k, perakende ve tar\u0131m gibi geni\u015f kapsaml\u0131 alanlarda makine \u00f6\u011frenimi geli\u015ftirmek isteyen yapay zeka \u015firketleri i\u00e7in buradan y\u00fcksek kaliteli veriler elde edilebilir.<\/p>","protected":false},"excerpt":{"rendered":" Medical Image Annotation: A Key Role in AI Medical Diagnostics AI in healthcare is more common with the development of more efficient computer vision-based machine learning models. With the machine learning algorithm, more training data will be used. This will allow the AI model to learn more variants and make it easier for healthcare professionals […]<\/p>","protected":false},"author":3,"featured_media":14328,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"footnotes":""},"categories":[1],"tags":[],"class_list":["post-2879","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-data-annotation"],"blocksy_meta":[],"featured_image_urls":{"full":["https:\/\/www.datalabelify.com\/wp-content\/uploads\/2021\/11\/Medical-Image-Annotation.jpg",2240,1260,false],"thumbnail":["https:\/\/www.datalabelify.com\/wp-content\/uploads\/2021\/11\/Medical-Image-Annotation-150x150.jpg",150,150,true],"medium":["https:\/\/www.datalabelify.com\/wp-content\/uploads\/2021\/11\/Medical-Image-Annotation-300x169.jpg",300,169,true],"medium_large":["https:\/\/www.datalabelify.com\/wp-content\/uploads\/2021\/11\/Medical-Image-Annotation-768x432.jpg",768,432,true],"large":["https:\/\/www.datalabelify.com\/wp-content\/uploads\/2021\/11\/Medical-Image-Annotation-1024x576.jpg",1024,576,true],"1536x1536":["https:\/\/www.datalabelify.com\/wp-content\/uploads\/2021\/11\/Medical-Image-Annotation-1536x864.jpg",1536,864,true],"2048x2048":["https:\/\/www.datalabelify.com\/wp-content\/uploads\/2021\/11\/Medical-Image-Annotation-2048x1152.jpg",2048,1152,true],"trp-custom-language-flag":["https:\/\/www.datalabelify.com\/wp-content\/uploads\/2021\/11\/Medical-Image-Annotation-18x10.jpg",18,10,true],"ultp_layout_landscape_large":["https:\/\/www.datalabelify.com\/wp-content\/uploads\/2021\/11\/Medical-Image-Annotation-1200x800.jpg",1200,800,true],"ultp_layout_landscape":["https:\/\/www.datalabelify.com\/wp-content\/uploads\/2021\/11\/Medical-Image-Annotation-870x570.jpg",870,570,true],"ultp_layout_portrait":["https:\/\/www.datalabelify.com\/wp-content\/uploads\/2021\/11\/Medical-Image-Annotation-600x900.jpg",600,900,true],"ultp_layout_square":["https:\/\/www.datalabelify.com\/wp-content\/uploads\/2021\/11\/Medical-Image-Annotation-600x600.jpg",600,600,true],"yarpp-thumbnail":["https:\/\/www.datalabelify.com\/wp-content\/uploads\/2021\/11\/Medical-Image-Annotation-120x120.jpg",120,120,true]},"post_excerpt_stackable":" Medical Image Annotation: A Key Role in AI Medical Diagnostics AI in healthcare is more common with the development of more efficient computer vision-based machine learning models. With the machine learning algorithm, more training data will be used. This will allow the AI model to learn more variants and make it easier for healthcare professionals to predict outcomes with greater accuracy. Annotated medical images can be used to detect diseases or other ailments through machines to make the training data more useful and productive. Annotating medical images is a process that creates such data with acceptable accuracy. What is Medical…<\/p>\n","category_list":"Data Annotation<\/a>","author_info":{"name":"Parth P","url":"https:\/\/www.datalabelify.com\/tr\/author\/soeuidhae\/"},"comments_num":"0 comments","_links":{"self":[{"href":"https:\/\/www.datalabelify.com\/tr\/wp-json\/wp\/v2\/posts\/2879","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.datalabelify.com\/tr\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.datalabelify.com\/tr\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.datalabelify.com\/tr\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/www.datalabelify.com\/tr\/wp-json\/wp\/v2\/comments?post=2879"}],"version-history":[{"count":8,"href":"https:\/\/www.datalabelify.com\/tr\/wp-json\/wp\/v2\/posts\/2879\/revisions"}],"predecessor-version":[{"id":3083,"href":"https:\/\/www.datalabelify.com\/tr\/wp-json\/wp\/v2\/posts\/2879\/revisions\/3083"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.datalabelify.com\/tr\/wp-json\/wp\/v2\/media\/14328"}],"wp:attachment":[{"href":"https:\/\/www.datalabelify.com\/tr\/wp-json\/wp\/v2\/media?parent=2879"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.datalabelify.com\/tr\/wp-json\/wp\/v2\/categories?post=2879"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.datalabelify.com\/tr\/wp-json\/wp\/v2\/tags?post=2879"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}\n