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

Description: Explainable AI in Healthcare and Medicine by Arash Shaban-Nejad, Martin Michalowski, David L. Buckeridge Estimated delivery 3-12 business days Format Hardcover Condition Brand New Description This book highlights the latest advances in the application of artificial intelligence and data science in health care and medicine. Publisher Description 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. Details ISBN 3030533514 ISBN-13 9783030533519 Title Explainable AI in Healthcare and Medicine Author Arash Shaban-Nejad, Martin Michalowski, David L. Buckeridge Format Hardcover Year 2020 Pages 344 Edition 1st Publisher Springer Nature Switzerland AG GE_Item_ID:137567009; About Us Grand Eagle Retail is the ideal place for all your shopping needs! With fast shipping, low prices, friendly service and over 1,000,000 in stock items - you're bound to find what you want, at a price you'll love! Shipping & Delivery Times Shipping is FREE to any address in USA. Please view eBay estimated delivery times at the top of the listing. Deliveries are made by either USPS or Courier. We are unable to deliver faster than stated. International deliveries will take 1-6 weeks. NOTE: We are unable to offer combined shipping for multiple items purchased. This is because our items are shipped from different locations. Returns If you wish to return an item, please consult our Returns Policy as below: Please contact Customer Services and request "Return Authorisation" before you send your item back to us. Unauthorised returns will not be accepted. Returns must be postmarked within 4 business days of authorisation and must be in resellable condition. Returns are shipped at the customer's risk. We cannot take responsibility for items which are lost or damaged in transit. For purchases where a shipping charge was paid, there will be no refund of the original shipping charge. Additional Questions If you have any questions please feel free to Contact Us. Categories Baby Books Electronics Fashion Games Health & Beauty Home, Garden & Pets Movies Music Sports & Outdoors Toys

Price: 218.25 USD

Location: Fairfield, Ohio

End Time: 2024-10-29T02:48:29.000Z

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

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Restocking Fee: No

Return shipping will be paid by: Buyer

All returns accepted: Returns Accepted

Item must be returned within: 30 Days

Refund will be given as: Money Back

ISBN-13: 9783030533519

Book Title: Explainable AI in Healthcare and Medicine

Number of Pages: Xxii, 344 Pages

Language: English

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

Publisher: Springer International Publishing A&G

Subject: Engineering (General), Intelligence (Ai) & Semantics, General, Biomedical

Publication Year: 2020

Item Weight: 25.3 Oz

Type: Textbook

Item Length: 9.3 in

Author: Martin Michalowski

Subject Area: Computers, Technology & Engineering, Medical

Series: Studies in Computational Intelligence Ser.

Item Width: 6.1 in

Format: Hardcover

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