Classification of Hospital of the Future Applications using Machine Learning

Effective health management is critical to ensure patients have access to necessary healthcare services. There are a number of challenges that can limit the provision of medical treatment, including a shortage of healthcare professionals, limited resources, and geographical barriers. Hospital of the Future (HoF) incorporates a number of technologies and innovations to improve the delivery of healthcare services and support effective health management. 5G network slicing has the potential to greatly enhance the capabilities of hospitals and the delivery of healthcare services. The network can be sliced into three main services; eMBB, mMTC, and URLLC. This paper presented a comparison of various supervised machine learning models in predicting the three network services. The classification for the slices is based on HoF applications’ requirements. Deep learning model has the highest accuracy of 100% with total runtime of 85.7s and lowest standard deviation value. In comparison with other machine learning models, deep learning is the best model in predicting 5GHoF slices.