Excel International Journal of Technology, Engineering & Management

ISSN : (Print): 2348–0378 |
(Online): 2349–8455

2.5

CiteScore

8.8

Global Impact Factor

Artificial Intelligence and Machine Learning in Telemedicine: Advancing Diagnostics and Personalized Healthcare

Paper ID: EIJTEM_2024_11_4_54-57

Author's Name: Sai Surya Varshika Dandyala, Dr. Praveen Kumar yechuri

Volume: 11

Issue: 4

Year: 2024

Page No: 54-57

Abstract:

The integration of Artificial Intelligence (AI) and Machine Learning (ML) into telemedicine is transforming healthcare delivery through enhanced diagnostic accuracy, personalized treatment, and improved system efficiency. This paper builds on the foundational work of Kothamali et al. (2024), which examined the impact of AI and ML on telemedicine systems, exploring their applications and limitations. By reviewing contemporary literature and incorporating new datasets, this study identifies current advancements, evaluates challenges like data privacy and algorithmic bias, and suggests pathways for optimizing AI and ML integration in healthcare. This review aims to provide a comprehensive understanding of AI and ML’s role in advancing telemedicine, addressing both theoretical and practical dimensions.

Keywords: AI, ML

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