OBJECTIVE: This research aims to provide a literature review study and an in-depth analysis to (1) investigate the procedure and roles of remote diagnosis in telemedicine; (2) review the technical tools and technologies used in remote diagnosis; (3) review the diseases diagnosed remotely in telemedicine; (4) compose a crossover taxonomy among diseases, technologies, and telemedicine; (5) present lists of input variables, vital signs, data and output decisions already applied in remote diagnosis; (6) Summarize the performance assessment measures utilized to assess and validate remote diagnosis models; and (7) identify and categorize open research issues while providing recommendations for future advancements in intelligent remote diagnosis within telemedicine systems.
METHODS: A systematic search was conducted using online libraries for articles published from 1 January 2016 to 13 September 2023 in IEEE, PubMed, Science Direct, Springer, and Web of Science. Notably, searches were limited to articles in the English language. The papers examine remote diagnosis in telemedicine, the technologies employed for this function, and the ramifications of diagnosing patients outside hospital settings. Each selected study was synthesized to furnish proof about the implementation of remote diagnostics in telemedicine.
RESULTS: A new crossover taxonomy between the most important diagnosed diseases and technologies used for this purpose and their relationship with telemedicine tiers is proposed. The functions executed at each tier are elucidated. Additionally, a compilation of diagnostic technologies is provided. Additionally, open research difficulties, advantages of remote diagnosis in telemedicine, and suggestions for future research prospects that require attention are systematically organized and presented.
CONCLUSIONS: This study reviews the role of remote diagnosis in telemedicine, with a focus on key technologies and current approaches. This study highlights research challenges, provides recommendations for future directions, and addresses research gaps and limitations to provide a clear vision of remote diagnosis in telemedicine. This study emphasizes the advantages of existing research and opens the possibility for new directions and smart healthcare solutions.