Prediction of Medical Devices’s performances using Machine Learning Techniques

Poorly regulated and insufficiently controlled post-market surveillance of medical devices (MDs) poses a high risk on efficiency of patient diagnosis and treatments due to increased rate of incidents caused by them. To address this, automated systems based on machine learning techniques can be developed to predict performance of medical devices and possible failures which can affect performance.

To develop accurate prediction algorithms, data of safety and performance measurements (collected during periodical inspections) can be used.

Developed automated systems can be reliable and beneficial for healthcare institutions, for management of medical devices and planning of replacements and preventive/corrective maintenance, therefore for decreasing financial cost of MD management.