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Explainable AI in Healthcare and Medicine - 9783030533540

Description: Explainable AI in Healthcare and Medicine Please note: this item is printed on demand and will take extra time before it can be dispatched to you (up to 20 working days). Building a Culture of Transparency and Accountability Author(s): Arash Shaban-Nejad, Martin Michalowski, David L. Buckeridge Format: Paperback Publisher: Springer Nature Switzerland AG, Switzerland Imprint: Springer Nature Switzerland AG ISBN-13: 9783030533540, 978-3030533540 Synopsis 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.

Price: 111.67 GBP

Location: Aldershot

End Time: 2024-02-12T09:23:41.000Z

Shipping Cost: 38.43 GBP

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Explainable AI in Healthcare and Medicine - 9783030533540

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Book Title: Explainable AI in Healthcare and Medicine

Item Height: 235mm

Item Width: 155mm

Author: Arash Shaban-Nejad, David L. Buckeridge, Martin Michalowski

Publication Name: Explainable Ai in Healthcare and Medicine: Building a Culture of Transparency and Accountability

Format: Paperback

Language: English

Publisher: Springer Nature Switzerland A&G

Subject: Engineering & Technology, Computer Science

Publication Year: 2021

Type: Textbook

Number of Pages: 344 Pages

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