株式会社極東書店トップ商品一覧Artificial Intelligence and Cloud Computing Applications in Biomedical Engineering.

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Artificial Intelligence and Cloud Computing Applications in Biomedical Engineering.

Artificial Intelligence and Cloud Computing Applications in Biomedical Engineering.

・ISBN 978-1-041-01926-8 paper GB£ 56.99

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お気に入り
電子版あり 大学・学術機関向け電子ブック(eBook)ISBN 9781003617013
著者・編者H S, Madhusudhan / Gupta, Punit / Rawat, Pradeep Singh / Kumar Saini, Dinesh (eds.),
出版社 (Auerbach, UK)
出版年月2025
ページ数236 pp.
言語ENG
ニュース番号<A04-8811>

解説

Biomedical engineering is undergoing a transformation because of AI, which is allowing creative solutions that enhance patient outcomes, diagnosis, treatment planning, and healthcare delivery. Artificial Intelligence and Cloud Computing Applications in Biomedical Engineering examines the salient characteristics of AI in biomedical engineering, highlighting its practical applications and new directions. Highlights of the book include:

  • Genome sequence and visualization
  • The role of AI and cloud in detection of diseases
  • Nature-inspired algorithms for disease detection
  • Frameworks for disease classification

With a focus on designing AI techniques for disease detection, the book explores the role of AI in biomedical engineering. It discusses how machine learning (ML) and deep learning (DL) are at the heart of AI applications in biomedical engineering. ML algorithms, particularly those based on neural networks, enable computers to learn from large datasets, identify patterns, and make predictions or decisions without explicit programming, and implementing ML algorithms is a focus of the book. Another focus is on DL, a subset of ML, and how it uses multi-layered neural networks to achieve high accuracy in such complex tasks as image and speech recognition. Biomedical engineering generates massive amounts of data from medical imaging, genomic sequencing, wearable devices, electronic health records (EHR), and other sources. This book also discusses AI-driven big data analytics, which allows researchers and clinicians to derive from data meaningful insights, aiding in early disease detection, personalized treatment plans, and patient monitoring.