Your team has developed a custom TensorFlow model designed to identify diagnostic images that require further analysis and medical support. The model demonstrated high accuracy during the testing phase using a comprehensive dataset. However, upon deployment in a real-world hospital setting, the medical staff reports significant dissatisfaction with the model's performance, noting that it frequently misses critical cases that require immediate attention. The hospital's IT infrastructure supports the model's computational requirements, and the data preprocessing pipeline is consistent with the testing phase. Given these constraints, what is the most likely reason for the discrepancy between the model's testing performance and its real-world application? Choose the best option.