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AI in Telemedicine: An Appraisal on Deep Learning-Based Approaches to Virtual Diagnostic Solutions (VDS)

arXiv 2208.04690 ↗First posted 31 Jul 2022cs.CY cs.AIcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 8 of its 40 references that are in the map. First posted on arXiv 31 Jul 2022.

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8 of 40 references.

References · 8

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  6. 2022Big Data and Analytics Implementation in Tertiary Institutions to Predict Students Performance in Nigeriacited by 3
  7. 2017Holistic Interstitial Lung Disease Detection using Deep Convolutional Neural Networks: Multi-label Learning and Unordered Poolingcited by 2
  8. 2022Hybrid Facial Expression Recognition (FER2013) Model for Real-Time Emotion Classification and Predictioncited by 2

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