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OverviewThis handbook on Artificial Intelligence (AI) in healthcare consists of two volumes. The first volume is dedicated to advances and applications of AI methodologies in specific healthcare problems, while the second volume is concerned with general practicality issues and challenges and future prospects in the healthcare context. The advent of digital and computing technologies has created a surge in the development of AI methodologies and their penetration to a variety of activities in our daily lives in recent years. Indeed, researchers and practitioners have designed and developed a variety of AI-based systems to help advance health and well-being of humans. In this first volume, we present a number of latest studies in AI-based tools and techniques from two broad categories, viz., medical signal, image, and video processing as well as healthcare information and data analytics in Part 1 and Part 2, respectively. These selected studies offer readers practical knowledge and understanding pertaining to the recent advances and applications of AI in the healthcare sector. Full Product DetailsAuthor: Chee-Peng Lim , Ashlesha Vaidya , Kiran Jain , Virag U. MahorkarPublisher: Springer Nature Switzerland AG Imprint: Springer Nature Switzerland AG Edition: 1st ed. 2022 Volume: 211 Weight: 0.875kg ISBN: 9783030791605ISBN 10: 3030791602 Pages: 456 Publication Date: 18 September 2021 Audience: Professional and scholarly , Professional & Vocational Format: Hardback Publisher's Status: Active Availability: Manufactured on demand ![]() We will order this item for you from a manufactured on demand supplier. Table of ContentsAdvances in artificial intelligence for the identification of epileptiform discharges.- Characterizing EEG electrodes in directed functional brain networks using normalized transfer entropy and page rank.- Autistic verbal behaviour language parameterization.- Case studies to demonstrate real-world applications in ophthalmic image analysis.- Segmentation of petri plate images for automatic reporting of urine culture tests.- Repurposing routine imaging for cancer biomarker discovery using machine learning.ReviewsAuthor Information
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