Addressing the challenges of AI-based telemedicine: Best practices and lessons learned

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Abstract

Telemedicine is the use of technology to provide healthcare services and information remotely, without requiring physical proximity between patients and healthcare providers. The coronavirus disease 2019 (COVID-19) pandemic has accelerated the rapid growth of telemedicine worldwide. Integrating artificial intelligence (AI) into telemedicine has the potential to enhance and expand its capabilities in addressing various healthcare needs, such as patient monitoring, healthcare information technology (IT), intelligent diagnosis, and assistance. Despite the potential benefits, implementing AI in telemedicine presents challenges that can be overcome with physician-guided implementation. AI can assist physicians in decision-making, improve healthcare delivery, and automate administrative tasks. To ensure optimal effectiveness, AI-powered telemedicine should comply with existing clinical practices and adhere to a framework adaptable to various technologies. It should also consider technical and scientific factors, including trustworthiness, reproducibility, usability, availability, and cost. Education and training are crucial for the appropriate use of new healthcare technologies such as AI-enabled telemedicine. This article examines the benefits and limitations of AI-based telemedicine in various medical domains and underscores the importance of physician-guided implementation, compliance with existing clinical practices, and appropriate education and training for healthcare providers.

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Sharma, S., Rawal, R., & Shah, D. (2023, January 1). Addressing the challenges of AI-based telemedicine: Best practices and lessons learned. Journal of Education and Health Promotion. Wolters Kluwer Medknow Publications. https://doi.org/10.4103/jehp.jehp_402_23

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