Year: 2024
Type: article
Abstract: Chronic Obstructive Pulmonary Disease (COPD) remains a major global health challenge, requiring innovative approaches for early diagnosis and effective management. The integration of Artificial Intelligence (AI) in COPD care presents significant advancements in early detection, personalized treatment, and disease monitoring. This study investigates AI-driven methodologies, including machine learning and predictive analytics, to enhance diagnostic accuracy and clinical decision-making. Through data preprocessing, feature engineering, and model training, an AI-based predictive framework was developed. The results demonstrate that AI models achieve a classification accuracy of 92.3%, significantly improving diagnostic precision and patient outcomes. Additionally, AI-driven decision support systems show promise in optimizing individualized treatment plans, facilitating proactive COPD management. However, challenges such as data availability, model interpretability, and ethical considerations must be addressed for broader clinical adoption. This research highlights AI’s transformative potential in COPD care and outlines future directions for its integration into healthcare systems.
Authors: Muhammad Nadeem Nadir, Asad Hayat, Junaid Abdullah Mansoor
Language: English
Subfield: Pulmonary and Respiratory Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
OpenAlex ID: W4408556104