Predicting Length of Stay in Ophthalmology Patients: A Neural Network Approach

Hospitalization duration after ophthalmic surgery varies widely, affecting costs, resource use, and outcomes. Length of stay (LOS) is key for hospital efficiency and patient management. Prolonged stays raise expenses and strain capacity, while early discharge risks complications. Accurate LOS prediction helps optimize care and reduce costs. This study developed a machine learning model to estimate LOS for ophthalmic surgery patients at A.O. "A. Cardarelli" in Naples, Italy. Using neural networks and decision tree-based models, we evaluated their predictive accuracy, highlighting AI's potential to improve planning and care in ophthalmology.