Survival Classification İn Heart Failure Patients By Neural Network-Based Crocodile And Egyptian Plover (Cep) Optimization Algorithm

Key Points

• The aim is to classify survival outcomes in heart failure patients using a neural network-based optimization algorithm.
• Neural network models were utilized for analyzing survival outcomes.
• An optimization algorithm, specifically the Crocodile and Egyptian Plover (CEP) method, was applied for improved classification.
• Data from heart failure patients were used to train and validate the model.
• The classifier achieved high accuracy in predicting survival rates in heart failure patients.
• Significant improvement in classification metrics was noted compared to traditional methods.