A Comprehensive Approach to Predict Chronic Impairment of the Pulmonary System Through the Application of Artificial Neural Network Algorithm
Adisree. R1, Mohamed Javed Khan A.2
1Adisree. R., Department of Computer Science and Engineering, SRM Institute of Science and Technology, Ramapuram, Chennai (Tamil Nadu), India.
2Mohamed Javed Khan A., Department of Computer Science and Engineering, SRM Institute of Science and Technology, Ramapuram, Chennai (Tamil Nadu), India.
Manuscript received on 12 October 2024 | Revised Manuscript received on 23 October 2024 | Manuscript Accepted on 15 November 2024 | Manuscript published on 30 November 2024 | PP: 24-27 | Volume-13 Issue-4, November 2024 | Retrieval Number: 100.1/ijrte.D817013041124 | DOI: 10.35940/ijrte.D8170.13041124
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: COPD is a respiratory condition with airflow restriction and increased inflammation in the air passages. It is the main reason for sickness and death around the world, where it requires sophisticated diagnostic instruments. This research examines how Artificial Neural Networks (ANN) can be used to predict COPD. The clinical dataset has been trained and validated; ANN achieved over 93.75% accuracy. Our findings show that the ANN model is effective in aiding early COPD detection, which could enhance clinical decision-making and patient results.
Keywords: Chronic Obstructive Pulmonary Disease, Artificial Neural Networks, Forced Expiratory Volume, Forced Vital Capacity.
Scope of the Article: Artificial Intelligence & Methods