AI-Based Model Design for Prediction of COPD Grade from Chest X-Ray Images: A Model Proposal (COPD-GradeNet)

Yıl 2024, , 325 - 338, 11.07.2024

Serdar Abut

https://doi.org/10.21605/cukurovaumfd.1514012

Öz

Chronic Obstructive Pulmonary Disease (COPD) ranks high among the leading causes of death, particularly in middle- and low-income countries. Early diagnosis of COPD is challenging, with limited diagnostic methods currently available. In this study, a artificial intelligence model named COPD-GradeNet is proposed to predict COPD grades from radiographic images. However, the model has not yet been tested on a dataset. Obtaining a dataset including spirometric test results and chest X-ray images for COPD is a challenging process. Once the proposed model is tested on an appropriate dataset, its ability to predict COPD grades can be evaluated and implemented. This study may guide future research and clinical applications, emphasizing the potential of artificial intelligence-based approaches in the diagnosis of COPD.

Anahtar Kelimeler

Artificial intelligence, COPD, Deep learning, Transfer learning, Medical image processing

Akciğer Grafilerinden KOAH Derecesinin Tahmin Edilmesi için Yapay Zeka Temelli Model Tasarımı: Bir Model Önerisi (COPD-GradeNet)

Öz

Kronik Obstrüktif Akciğer Hastalığı (KOAH), özellikle orta ve düşük gelirli ülkelerde ölüm nedenleri arasında üst sıralarda yer alır. KOAH'ın erken teşhisi zordur ve mevcut tanı yöntemleri sınırlıdır. Bu çalışmada, radyografi görüntülerinden KOAH derecelerini tahmin etmek için bir yapay zeka modeli olan COPD-GradeNet önerilmektedir. Ancak, model henüz bir veri seti üzerinde test edilmemiştir. KOAH'ın spirometrik test sonuçları ve akciğer röntgen görüntüleri gibi bir veri setinin elde edilmesi zorlu bir süreçtir. Önerilen modelin uygun bir veri setiyle test edilmesi halinde, KOAH derecelerini tahmin etme yeteneğinin değerlendirilip uygulanabileceği düşünülmektedir. Bu çalışma, gelecekteki araştırmalara ve klinik uygulamalara yol gösterebilir, KOAH teşhisinde yapay zeka tabanlı yaklaşımların potansiyelini vurgulayabilir.

Anahtar Kelimeler

Yapay zeka, KOAH, Derin öğrenme, Transfer öğrenme, Medikal görüntü işleme

Kaynakça

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