AI Innovations: Transforming the Future of Chronic Obstructive Pulmonary Disease Treatment

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.

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Publication Details

Journal
Journal of Computational Science and Applications (JCSA) ISSN 3079-0867 (Onilne)
Published
2024-12-01
DOI
https://doi.org/10.51846/jcsa.v1i2.3572
Citations
1
Primary Topic
Chronic Obstructive Pulmonary Disease (COPD) Research
Type
article
Field-Weighted Citation Impact
0.42
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article

AI Innovations: Transforming the Future of Chronic Obstructive Pulmonary Disease Treatment

Junaid Mansoor, Muhammad Nadeem Nadir, Asad Hayat
1 citations
Journal of Computational Science and Applications (JCSA) ISSN 3079-0867 (Onilne)
Chronic Obstructive Pulmonary Disease (COPD) Research
0.42
article

AI Innovations: Transforming the Future of Chronic Obstructive Pulmonary Disease Treatment

Junaid Mansoor, Muhammad Nadeem Nadir, Asad Hayat
article en
1 citations

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.

Journal of Computational Science and Applications (JCSA) ISSN 3079-0867 (Onilne)Vol. 1(2)
Capital University of Science and Technology (PK), Taiyuan University of Science and Technology (CN), University of Management and Technology (PK)
Openalex Percentile: Top 29%
Chronic Obstructive Pulmonary Disease (COPD) Research
0.42
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AI Innovations: Transforming the Future of Chronic Obstructive Pulmonary Disease Treatment — Junaid Mansoor, Muhammad Nadeem Nadir, et al. · Journal of Computational Science and Applications (JCSA) ISSN 3079-0867 (Onilne) (2024) | TGRS Research Map | TGRS