Yapay Zekanın Kardiyovasküler Hastalıklar Alanında Uygulanması Hem Teşhis Hem de Tedavi Yönlerine Odaklanmaktadır.

Year 2024, , 22 - 35, 14.06.2024

Lütfü Aşkın , Esra Polat , Yusuf Hoşoğlu , Okan Tanrıverdi

https://doi.org/10.46871/eams.1438927

Abstract

Yapay zeka (YZ), tıp alanında gelişmiş bilgisayar algoritmaları kullanarak büyük veri tabanlarından bilgi almak için kullanılır. YZ, kalp yetmezliği, atriyal fibrilasyon, kalp kapak hastalığı, hipertrofik kardiyomiyopati, konjenital kalp hastalığı ve diğerleri gibi durumlar da dahil olmak üzere kardiyovasküler hastalıkların (KVH'ler) tanımlanmasını ve yönetimini hızlandırma potansiyeline sahiptir. Klinik bir perspektiften bakıldığında, YZ KVH tanısını geliştirir, yardımcı araçların kullanışlılığını artırır, farklı hastalık türlerinin sınıflandırılmasına ve tanımlanmasına yardımcı olur ve sonuçların doğru tahmin edilmesini sağlar. Kapsamlı sağlık verilerinden küçük bağlantılar çıkarmak için tasarlanan son teknoloji YZ algoritmalarının, önceki yöntemlere kıyasla daha zorlu görevleri ele alması beklenmektedir. Bu araştırmanın amacı, YZ'nin KVH'lerdeki mevcut kullanımlarını vurgulamak ve böylece bilgisayar bilimleri konusunda çok az bilgisi olan doktorları daha derin bir anlayış kazanmaları ve klinik uygulamada YZ algoritmalarını etkili bir şekilde kullanmaları için donatmaktır.

Keywords

ileri bilgisayar algoritmaları, yapay zeka, kardiyovasküler hastalıklar

The Application of Artificial Intelligence in the Field of Cardiovascular Diseases Focuses on Both Diagnostic and Therapeutic Aspects.

Abstract

Artificial intelligence (AI) is used in the field of medicine to retrieve information from large databases by using advanced computer algorithms. AI has the potential to accelerate the identification and management of cardiovascular diseases (CVDs), including conditions such as heart failure, atrial fibrillation, valvular heart disease, hypertrophic cardiomyopathy, congenital heart disease, and several others. From a clinical perspective, AI enhances the diagnosis of CVD, increases the usefulness of auxiliary tools, aids in stratifying and identifying different types of diseases, and enables accurate prediction of outcomes. State-of-the-art AI algorithms, designed to extract minute connections from extensive healthcare data, are anticipated to address more challenging tasks compared to earlier methods. The goal of this research is to emphasize the current uses of AI in CVDs, thereby equipping doctors with little knowledge in computer science to gain a deeper understanding and effectively use AI algorithms in clinical practice.

Keywords

advanced computer algoritms, artificial intelligence, cardiovascular diseases

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