Sağlıkta Yapay Zeka Uygulamasının 24 Büyük Zorluğu
Derleme Makale
DOI:
https://doi.org/10.5281/zenodo.8340188Anahtar Kelimeler:
Yapay Zeka, Radyoloji, Öğrenme Eğrisi, Derin Öğrenme, Sağlık MerkezleriÖzet
Giriş: Yapay Zeka'nın (YZ) tıbbi disiplinlere entegrasyonu önemli bir potansiyel göstermiştir. Ancak, AI'ın potansiyeli ve vaatleri hakkında coşkulu bir literatür bolluğu olmasına rağmen, özellikle tıbbi teşhislerde, pratik tıbbi ortamlarda yaygın olarak benimsenmesiyle ilişkilendirilen birçok zorluk hakkında tartışma eksikliği vardır.
Amaç: Bu çalışma, tıbbi uygulamada yapay zeka teknolojilerini benimseme ile ilişkilendirilen zorlukları ayrıntılı olarak analiz etmeyi amaçlamaktadır. Bu teknolojinin ilerlemesi hakkında gerçekçi bir perspektif sunar, kontrol altındaki laboratuvar koşullarında prototiplerin ve teknolojik göstericilerin ilerlemesini öne çıkaran aşırı idealize edilmiş görüşlere karşı koyar.
Yöntem: Bu çalışmanın araştırma tasarımı, belge analizi/inceleme yöntemine dayanmaktadır. Bu bağlamda, Google Scholar, PubMed, BioMed Central, Cochrane ve çeşitli bilimsel veritabanları gibi platformlar aracılığıyla birçok bilimsel çalışma keşfedildi. Makalelere erişim sağlandı, ardından dikkatli veri analizi ve değerlendirmeleri yapıldı. İncelenen her zorluk için arama kriterleri ayarlandı.
Bulgular: Toplamda 24 önemli zorluk tespit edildi, bunlar iç içe geçmiş ve tıbbi alandaki AI tabanlı gelişmelerin olgunluk seviyesini örneklendiren örneklerle ayrıntılı olarak incelendi. Bu zorluklar doğalarına göre üç ana kategoriye ayrılmıştır. Her bölüm, bağımsız olarak anlaşılabilir bir şekilde yazılmıştır. Gelecek, tıp ve yapay zeka arasındaki sinerjiden kaynaklanan dikkat çekici ilerlemeleri vurgulayan sayısız makale ile büyük vaatlerde bulunmaktadır. Bu nedenle, faydaları, mevcut sınırlamaları ve bunların üstesinden gelmek için yeni yolları ayırt edebilmek için eleştirel düşünmeyi geliştirmek gerekmektedir.
Sonuç: Zorlukların hiçbiri diğerlerinden daha önemli değildir. Tıpta yapay zekanın evrimi, hem hastalar hem de tıbbi uzmanlar için faydaları en üst düzeye çıkarmak için stratejiler kullanarak bu zorlukların kolektif olarak üstesinden gelinmesini gerektirir.
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