Akciğer ve Meme Kanserinde Yapay Zeka: LLM ve LVM ile Öneriler

Yıl 2025, Cilt: 8 Sayı: 5, 2574 - 2593, 15.12.2025

Berra Öz , Ali Hakan Isık

https://doi.org/10.47495/okufbed.1606660

Öz

Kanser, vücut hücrelerinin kontrolsüz bir şekilde büyüyüp çoğalması sonucunda oluşan bir hastalıktır. Akciğer ve meme kanseri, dünya genelinde en sık görülen kanser türlerinden biridir ve bu nedenle kanser teşhisi, hastalığın erken evrelerinde tespit edilmesi ve tedaviye başlanması açısından kritik bir öneme sahiptir. Geleneksel teşhis yöntemleri zaman zaman yeterince hassas sonuçlar vermemektedir. Bu bağlamda, yapay zekâ destekli kanser teşhisi önemli bir rol oynamaktadır. Yapay zekâ daha geniş bir veri yelpazesini ele alarak kanser teşhisinde fark edilemeyebilecek önemli ayrıntıları algılayabilmekte ve belirli kanser türlerini erken aşamada tespit edebilmektedir. Bu derleme makalesi, 2020 ile 2023 yılları arasında yapılan çalışmalarda, akciğer ve meme kanseri tanısında kullanılan makine öğrenimi ve derin öğrenme algoritmalarının detaylı bir incelemesini sunmayı ve bu algoritmaların akciğer ve meme kanseri teşhisi performanslarını değerlendirmeyi amaçlamaktadır. Bu çalışmada 30 makale incelenmiş ve literatür taraması sonucunda LLM (Large Language Model) ve LVM (Large Vision Model)'nin onkoloji alanındaki etkinliği analiz edilmiştir. Bu modellerin potansiyelini artırmak ve onkoloji alanındaki uygulamalarda etkin bir şekilde kullanımının genişletilebilmesi amacıyla çeşitli önerilerde bulunulmuştur. Bu çalışmanın, klinik uygulamalarda algoritmaların performansını değerlendirmek için önemli bir rehber olabileceği ve LLM ile LVM’lerin tıbbi uygulamalardaki potansiyelini vurgulayarak bu alandaki ilerlemelerin önemini ve etkisini geniş bir kitleye duyurabileceği düşünülmektedir.

Anahtar Kelimeler

Derin Öğrenme , Makine Öğrenmesi , Large Language Model , Large Vision Model

Artificial Intelligence in Lung and Breast Cancer: Recommendations with LLM and LVM

Öz

Cancer is a disease caused by the uncontrolled growth and proliferation of body cells. Lung and breast cancers are among the most common types of cancer worldwide. Therefore, early detection of cancer and timely initiation of treatment are critically important. Traditional diagnostic methods may sometimes struggle to provide accurate results. In this context, artificial intelligence (AI)-assisted cancer diagnosis plays a pivotal role. AI can analyze a broader range of data and detect critical details that might otherwise go unnoticed, enabling the early detection of specific types of cancer. This review article aims to provide a detailed examination of machine learning (ML) and deep learning (DL) algorithms used in the diagnosis of lung and breast cancer in studies conducted between 2020 and 2023. A total of 30 studies were reviewed, and the effectiveness of Large Language Models (LLMs) and Large Vision Models (LVMs) in oncology was analyzed based on the literature. To further enhance the potential of these models and expand their effective use in oncology applications, various recommendations are proposed. It is thought that the study can be an important guide for evaluating the performance of algorithms in clinical applications and can convey the importance and impact of advances in this field to a wider audience by emphasizing the potential of LLMs and LVMs in medical applications.

Anahtar Kelimeler

Deep Learning , Machine Learning , Large Language Model , Large Vision Model

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