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Article detail · 2024

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

Journal

Çukurova Üniversitesi Mühendislik Fakültesi Dergisi

ISSN 2757-9255

YÖKSİS OpenAlex Open access · diamond TR Index Citations 7 Percentile 84.7% FWCI 1.78
Year
2024
Type
article

Data source split

  • YÖKSİS YÖKSİS article record
  • YÖKSİS venue Çukurova Üniversitesi Mühendislik Fakültesi Dergisi
  • OpenAlex OpenAlex enrichment (abstract, citations, topics)

Abstract

OpenAlex · English

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.

Topics

Citations

OpenAlex cited_by_count. Not a WoS or Scopus citation count; those sources have no separate column here.

7 citations

OpenAlex cited_by_count (cache / database)

2 publications in the local catalog that cite this work (OpenAlex reference match; not the full global list).

  1. IoU-Based Anchor Box Estimation for Enhanced Lung Region Localization in Chest X-rays Using YOLO v4 2025 Citations 1 · OpenAlex
  2. Classification of Atelectasis from Chest X-Ray Images Using Deep Learning Approaches 2026 Citations 0 · OpenAlex

Authors

  1. SERDAR ABUT KAYSERİ ÜNİVERSİTESİ