Aug 8, 2022 · A solution taxonomy of EXAI in Healthcare 5.0 is proposed, and operational challenges are presented. A supported case study on electrocardiogram ...
The proposed research scheme provides end-to- end explainability for medical imaging applications through AI and federated transfer learning (FTL) in a ...
Aug 7, 2022 · The case-study is supported through experimental validation. The analysis proves the efficacy of EXAI in health setups that envisions real-life ...
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This transformative synergy presents opportunities to enhance diagnostic accuracy, treatment recommendations, and patient outcomes, while simultaneously posing ...
Feb 22, 2024 · The advent of Explainable AI (XAI) in healthcare, ; often referred to as Healthcare 5.0, presents both ; significant opportunities and challenges.
Explainable AI (XAI) has emerged as a promising approach to address this challenge by providing clear and interpretable explanations for the predictions and ...
This paper explores the evolving landscape of XAI in healthcare, highlighting its potential to improve patient outcomes, reduce errors, and optimize resource ...
The study discusses Healthcare 5.0's potentials and opportunities, including personalised medicine, sophisticated diagnostics, telemedicine, ...
The advent of Explainable AI (XAI) in healthcare, often referred to as Healthcare 5.0, presents both significant opportunities and challenges.
Dec 22, 2023 · This paper navigates through the complexities and potentials of AI in healthcare, emphasising the necessity of explainability, trustworthiness, ...