Use of Artificial Intelligence and Big Data Management in Healthcare Institutions

Abstract

Tıbbi YZ, tıbbın araştırma ve uygulama alanlarındaki sıcak konulardan biridir. Çeşitli araştırmalar, YZ'nin tıbbi kullanımları için önemli bir etik zorluk olarak gizlilikten bahsetmektedir. İyi haber şu ki, YZ araçlarının çoğu hekimin yerini almak için değil, onlara yardımcı olmak için tasarlanmıştır. Bu, etik zorlukları azaltırken, hepsini ortadan kaldırmamaktadır. Araştırmacılar, tıbbi YZ'nin etik kullanımları konusunda fikir birliğinden uzak olsak da, temel ilkeler üzerinde aşağı yukarı bir anlaşmaya sahip olduğumuzu belirtiyor. YZ'yi eğitmek için kullanılacak tıbbi veriler dar bir hasta örneğinden geliyorsa, daha büyük gruplarda hata yapabilir. Öte yandan, diğer bazı sorunlar kullanıcılardan kaynaklanabilir. Bu nedenle, YZ okuryazarlığının geliştirilmesi gereklidir. Başka bir deyişle, çeşitli amaçlar için hangi YZ araçlarını kullanacaklarını öğrenmeleri gerekir. Tıbbi YZ'nin ilk versiyonlarını düşündüğümüzde, açıklama ve öğretim için mantıklı olduklarını, ancak klinik uygulama için bir asistan olarak başarısız olduklarını fark ediyoruz, ancak bu durum hızla değişiyor. Tıp öğrencileri tıbbi YZ'ye son derece olumlu yaklaşıyor ve insan doktorların yerini almayacağına ancak onları tamamlayacağına inanıyor. Radyoloji başta olmak üzere bir grup tıbbi alanda YZ'nin insan doktorlardan daha iyi performans göstereceğine dair gerçekçi bir endişe vardır. YZ kaygısı, YZ'yi kullanmanın algılanan zorluğundan da kaynaklanabilir. Tıbbi YZ'deki etik sorunlara bir çözüm, güvenilir YZ modelidir.

Keywords

• Yapay Zeka
• Medikal Yapay Zeka
• Yapay Zekanın Etik Kullanımı

Use of Artificial Intelligence and Big Data Management in Healthcare Institutions

Abstract

Medical AI is one of the hot topics in the research and applied fields of medicine. Various research mention privacy as a major ethical challenge for medical uses of AI. The good news is most of the AI tools are design to replace physician but to assist them. This reduces ethical challenges, while not eliminating all. Researchers state that although we are far from consensus in ethical uses of medical AI, we have more or less an agreement on key principles. If the medical data to be used to train AI is from a narrow sample of patients, it can err with larger groups. On the other hand, some other problems can be due to users. Thus, development of AI literacy is necessary. In other words, they have to learn which AI tools to use for various purposes. When we consider early versions of medical AI, we realize that they mad sense for explanation and teaching, but fail as an assistant for clinical practice, but this situation has been changing rapidly. Medical students are highly positive of medical AI, and believe that it will not replace but complement human doctors. There is a realistic anxiety that in a group of medical areas, especially radiology, AI will outperform human doctors. AI anxiety can also be due to perceived difficulty to use AI. A solution to ethical problems in medical AI is trustworthy AI model.

Keywords

• AI
• Ethical Uses of AI
• Medical AI

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