Klinik Mikrobiyoloji Laboratuvarinda Yapay Zeka Uygulamaları

Yıl 2024, Cilt: 9 Sayı: 2, 56 - 72

Erdoğan Yayla

https://doi.org/10.58854/jicm.1404800

Öz

Yapay zeka, klinik mikrobiyoloji bilişiminin giderek daha önemli bir bileşeni haline gelmektedir. Araştırmacılar, mikrobiyologlar, laboratuvar uzmanları ve tanı-teşhis uzmanları yapay zeka tabanlı testlerle ilgileniyor çünkü bu uygulamalar bir testin geri dönüş süresini, kalitesini ve maliyetini iyileştirme potansiyeline sahiptir. Laboratuvarda önem kazanan yapay zeka; tıbbi mikrobiyoloji ve enfeksiyon hastalıkları testlerinde çeşitli teknolojiler, görüntü analizleri ve MALDI-TOF-MS ile karar verme, tanımlama ve antimikrobiyal duyarlılık testlerini desteklemek amacıyla kullanılmaktadır. Enfeksiyonların tedavisi hızlı ve doğru tanımlamayı ve antimikrobiyal duyarlılık testini gerektirir. Modern yapay zeka (AI) ve makine öğrenimi (ML) yöntemleri görevlerini, uzman insan operatörlerin performansıyla karşılaştırılabilecek performans özellikleriyle tamamlayabiliyor. Sonuç olarak, birçok sağlık alanı, in vitro teşhisler de dahil olmak üzere bu teknolojileri birleştirir ve daha geniş anlamda laboratuvar tıbbı bu teknolojileri içerir. Bu teknolojiler hızla geliştirilmekte ve açıklanmaktadır, ancak kıyaslandığında şu ana kadarki uygulamalar sınırlıdır. Güvenilir ve gelişmiş makine öğrenimi tabanlı teknolojilerin uygulanmasını teşvik etmek için en iyi uygulamaları daha fazla oluşturmamız, bilgi sistemimizi ve iletişim altyapımızı geliştirmemiz gerekiyor. Klinik mikrobiyoloji laboratuvar topluluğunun katılımı, laboratuvar verilerinin yeterince erişilebilir olmasını, sağlam, güvenli ve klinik olarak etkili ML destekli klinik teşhislere ve bu tür uygulamalara dikkatli bir şekilde dahil edilmesini sağlamak için esastır ve bu tip teknolojik düzenlemeler mikrobiyoloji laboratuvarlarında gelecekte çığır açacaktır.

Anahtar Kelimeler

Mikrobiyoloji, Yapay zeka, Makine öğrenimi

Artificial Intelligence Applications In Clinical Microbiology Laboratory

Öz

Artificial intelligence is becoming an increasingly important component of clinical microbiology informatics. Researchers, microbiologists, laboratorians, and diagnosticians are interested in AI-based testing because these applications have the potential to improve the turnaround time, quality, and cost of a test. Artificial intelligence which has gained importance in the laboratory, is used to support decision-making, identification and antimicrobial susceptibility testing with various technologies, image analyses, and MALDI-TOF-MS in medical microbiology and in infectious disease testing. Treatment of infections requires rapid and accurate identification and antimicrobial susceptibility testing. Modern artificial intelligence (AI) and machine-learning (ML) methods can now complete tasks with performance characteristic comparable to those of expert human operators. As a result, many healthcare fields combine these technologies, including in vitro diagnostics and, more broadly laboratory medicine, incorporate these technologies. These technologies are rapidly being developed and disclosed, but by comparison, their application so far has been limited. We need to further establish best practices and improve our information system and communications infrastructure to promote the implementation of reliable and advanced machine learning-based technologies. İnvolvement of the clinical microbiology laboratory community is essential to ensure that laboratory data is adequately accessible and thoughtfully incorporated into robust, safe and clinically effective ML-supported clinical diagnoses and such technological adjustments will lead to future breakthroughs in microbiology laboratories.

Anahtar Kelimeler

Microbiology, Artificial intelligence, Machine-learning

Etik Beyan

Since this study was a review study, Ethics committee approval was not received.

Kaynakça

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