Paper Contents
Abstract
In the rapidly evolving landscape of healthcare, telemedicine has emerged as a pivotal tool, offering patients remote access to medical consultations and treatments. However, the trustworthiness of telemedicine platforms remains a concern, especially when artificial intelligence (AI) is employed to provide healthcare recommendations. This research paper delves into the application of Explainable AI (XAI) in telemedicine to enhance its trustworthiness and transparency. We investigate the current challenges faced by telemedicine platforms, particularly in the context of AI-driven recommendations, and explore how XAI can address these issues by offering clear, understandable explanations for AI-generated outputs. Our findings indicate that integrating XAI into telemedicine not only bolsters patient trust but also empowers healthcare professionals to make more informed decisions based on AI recommendations. We conclude by proposing a framework for the seamless integration of XAI in telemedicine platforms and discuss its potential implications for the future of remote healthcare.
Copyright
Copyright © 2023 Bhukya Ramesh. This is an open access article distributed under the Creative Commons Attribution License.
