AI in Telemedicine: An Appraisal on Deep Learning-Based Approaches to Virtual Diagnostic Solutions (VDS)
It provides an overview for researchers and practitioners in healthcare and AI, but is incremental as it synthesizes existing knowledge without presenting new results.
This paper conducts a descriptive study to explore AI implementations in telemedicine, focusing on deep learning-based approaches for Virtual Diagnostic Solutions (VDS), and reviews developments, prospects, and challenges in this area.
Advancements in Telemedicine as an approach to healthcare delivery have heralded a new dawn in modern Medicine. Its fast-paced development in our contemporary society is credence to the advances in Artificial Intelligence and Information Technology. This paper carries out a descriptive study to broadly explore AI's implementations in healthcare delivery with a more holistic view of the usability of various Telemedical Innovations in enhancing Virtual Diagnostic Solutions (VDS). This research further explores notable developments in Deep Learning model optimizations for Virtual Diagnostic Solutions. A further research review on the prospects of Virtual Diagnostic Solutions (VDS) and foreseeable challenges was also highlighted. Conclusively, this research gives a general overview of Artificial Intelligence in Telemedicine with a central focus on Deep Learning-based approaches to Virtual Diagnostic Solutions.