Explainable AI in Healthcare and Medicine : Building a Culture of Transparency and Accountability /

This book highlights the latest advances in the application of artificial intelligence and data science in health care and medicine. Featuring selected papers from the 2020 Health Intelligence Workshop, held as part of the Association for the Advancement of Artificial Intelligence (AAAI) Annual Conf...

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Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Shaban-Nejad, Arash (Editor), Michalowski, Martin (Editor), Buckeridge, David L. (Editor)
Format: eBook
Language:English
Published: Cham : Springer International Publishing : Imprint: Springer, 2021.
Edition:1st ed. 2021.
Series:Studies in Computational Intelligence, 914
Subjects:
Online Access:Connect to the full text of this electronic book
Description
Summary:This book highlights the latest advances in the application of artificial intelligence and data science in health care and medicine. Featuring selected papers from the 2020 Health Intelligence Workshop, held as part of the Association for the Advancement of Artificial Intelligence (AAAI) Annual Conference, it offers an overview of the issues, challenges, and opportunities in the field, along with the latest research findings. Discussing a wide range of practical applications, it makes the emerging topics of digital health and explainable AI in health care and medicine accessible to a broad readership. The availability of explainable and interpretable models is a first step toward building a culture of transparency and accountability in health care. As such, this book provides information for scientists, researchers, students, industry professionals, public health agencies, and NGOs interested in the theory and practice of computational models of public and personalized health intelligence.
Physical Description:1 online resource (XXII, 344 pages 110 illustrations, 84 illustrations in color.)
ISBN:9783030533526
ISSN:1860-9503 ;
DOI:10.1007/978-3-030-53352-6