Advancing Telemedicine with AI and Machine Learning: Enhancing Diagnostic Accuracy, Personalized Treatment, and Healthcare Efficiency

Abstract

The integration of Artificial Intelligence (AI) and Machine Learning (ML) in telemedicine is transforming healthcare systems, offering enhanced diagnostic accuracy, personalized treatment, and improved operational efficiency. This paper examines the role of AI and ML in advancing telemedicine, with a focus on diagnostic imaging, personalized medicine, and predictive analytics. The findings are drawn from a study conducted by Kothamali et al. (2024), which analyzed the application of AI models like ResNet-50 and BERT for diagnostic accuracy and therapy personalization. By comparing these advancements with existing literature, we underscore the benefits and challenges associated with AI-driven healthcare services.