@inbook{d1a3204abfdc41d2a7f893a4fbc3684c,
title = "Enhancing the Sustainability of Smart Healthcare Applications with XAI",
abstract = "This chapter first mentions three ways to enhance the sustainability of smart healthcare applications. Then, our experience from the COVID-19 pandemic tells us that the three goals can actually be achieved by applying explainable artificial intelligence (XAI). After introducing some basics of XAI, some representative cases of XAI applications in medicine and healthcare in the literature are discussed. Subsequently, two well-known applications of XAI in healthcare are detailed: an XAI application for enhancing the sustainability of a ubiquitous clinic recommendation system and another XAI application for enhancing the sustainability of an ANN-based diabetes diagnosis system. The two XAI applications enhanced both the understanding and trust of users, making them willing to use the system again and contributing to the sustainability of the smart healthcare applications.",
keywords = "COVID-19 pandemic, Diabetes diagnosis, Explainable artificial intelligence, Smart healthcare application, Sustainability, Ubiquitous clinic recommendation",
author = "Chen, {Tin Chih Toly}",
note = "Publisher Copyright: {\textcopyright} 2023, The Author(s).",
year = "2023",
doi = "10.1007/978-3-031-37146-2_5",
language = "English",
series = "SpringerBriefs in Applied Sciences and Technology",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "93--110",
booktitle = "SpringerBriefs in Applied Sciences and Technology",
address = "德國",
}
