Predicting Acute Respiratory Failure Using Fuzzy Classifier

Acute Respiratory Failure (ARF) is a critical condition that affects the respiratory system and causes it to malfunction, leading to high rates of morbidity and fatality when improperly diagnosed. Early ARF identification is essential because it enables prompt medical care. Disease prediction serves a variety of functions, from early, effective medical intervention to lifesaving and quality-of-life improvements. Fuzzy logic-based classification method for acute respiratory failure patients using a supervised neural network technique was introduced in this paper. The proposed model has achieved 97.7% accuracy.