Explainable AI: Methods, Frameworks, and Tools for Healthcare 5.0

The healthcare industry is enduring a transformative swing toward Healthcare 5.0, a concept that transcends the boundaries laid out by Healthcare 4.0 and prioritizes patient-centric wellness. Healthcare 5.0 emphasizes ambient control, real-time patient monitoring, privacy compliance, and wellness, all powered by emerging technologies. However, certain obstacles must be addressed before fully realizing Healthcare 5.0. The challenges include refining healthcare operational techniques, verifying prediction models, enhancing resilience, and developing ethical frameworks. Thus, the present work explores the healthcare progression and objectives. Further, it emphasizes the integration of medical science and technology for services within Healthcare 5.0. After that, demonstrate the pivotal role of artificial intelligence (AI) in prediction and decision support in Healthcare 5.0 along with the associated primary concerns. Consequently, the challenges are overcome with explainable AI (XAI) ensures transparency and trust among the patients and doctors. Thus, the study’s significance of XAI techniques in furnishing decision support in the context of Healthcare 5.0. Moreover, outlines the challenges that are associated with existing XAI techniques and future directions. Additionally, introduces available toolkits for experimental purposes and potential avenues for future development of XAI which aid researchers to explore healthcare-oriented applications and contribute to the advancement of the Healthcare 5.0 paradigm.