AI-Driven Innovations in Telemedicine: Bridging Gaps in Diagnostics and Personalized Care

Paper ID: EIJTEM_2024_11_2_19-22

Author's Name: Dr. Raju Dindigala, Dr Praveen Kumar yechuri

Volume: 11

Issue: 2

Year: 2024

Page No: 19-22

Abstract:

Artificial Intelligence (AI) and Machine Learning (ML) have emerged as transformative forces in telemedicine, addressing critical challenges in diagnostics, personalized care, and system efficiency. This paper cites the foundational work of "Artificial Intelligence and Machine Learning in Telemedicine: Advancing Diagnostics and Personalized Healthcare" (Kothamali et al., 2024), which explored the applications, limitations, and future prospects of AI and ML in telemedicine. Building on these insights, this study highlights recent advancements, examines case studies showcasing successful implementations, and discusses challenges such as algorithmic bias and data privacy. A detailed analysis of AI-driven applications in telemedicine underscores the potential of these technologies to enhance healthcare accessibility, equity, and outcomes. The findings emphasize the need for robust frameworks and interdisciplinary collaboration to fully realize the promise of AI in telemedicine.

Keywords: AI, Telemedicine, Personalized Care

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