Designing Automated Diagnostic Processes for Knee Injuries in Healthcare Organizations Using Deep Learning and MRI Images

Recent technological advancements have significantly transformed the diagnostic processes in healthcare organizations. The creation of automated diagnostic systems for knee injuries using deep learning and MRI imaging represents a substantial improvement in healthcare service quality. These systems allow for swift and accurate analysis of MRI images, facilitating precise identification and classification of knee injuries. Given the vast amount of medical data managed by healthcare institutions, such automation enhances operational efficiency and reduces response times. However, the successful implementation of these systems requires effective integration with existing Hospital Information Systems (HIS) and Picture Archiving and Communication Systems (PACS). This integration should be designed to optimize workflows and ensure the secure and efficient management of patient data.

کلیدواژه ها:

Deep Learning ، Knee MRI Imaging ، Automated Diagnostic Processes ، Healthcare Workflow Optimization