Telemedical networks are of strategic importance in transmitting the highly sensitive data for video consultation, for diagnosis and for monitoring of patients. But, some concerns that affect these are high latency, congestion, in-adequate bandwidths and rising incidences of cyber-crimes. This article offers a survey of such approaches for enhancing such networks coupled with a comparison of advanced technologies including graph theory, machine learning, bio-inspired algorithms; as well as current structures like cloud computing and edge computing. The performance of these technologies is compared across five criteria: The criteria adopted are latency, bandwidth efficiency, flexibility, security, and implementation complexity. The results reveal that those two technologies enables several benefits depending on the application areas encompassing rural and urban settings, As well as IoMT devices. Altogether, five solutions are presented, and moreover, theoretical development of a strategy that implies using all of them to enhance performance of telemedicine networks in diverse scenarios.