Description

Book Synopsis

This book is designed to consider the recent advancements in hospitals to diagnose various diseases accurately using AI-supported detection procedures. This work examines recent AI-supported disease detection techniques from prominent researchers and clinicians working in the medical imaging processing domain. Within this book, the integration of various AI methods, such as soft computing, machine learning, deep learning, and other related works will be presented. Real clinical images utilizing AI are incorporated. The book also includes several chapters on machine learning, convoluted neural networks, segmentation, and deep learning-assisted two-class and multi-class classification.


Key Features:


  • Implementation of machine-learning-assisted disease detection


  • Implementation of CNN (Convolutional Neural Networks) based medical image segmentation and assessment


  • Implementation of deep-learning-based medical data assessment


  • Hybridizing machine learning and deep learning features to enhance detection accuracy


Frontiers of Artificial Intelligence in Medical

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    £108.00

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    RRP £120.00 – you save £12.00 (10%)

    Order before 4pm today for delivery by Tue 23 Jun 2026.

    A Hardback by Navid Razmjooy, V Rajinikanth

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      Publisher: Institute of Physics Publishing
      Publication Date: 12/29/2022 12:00:00 AM
      ISBN13: 9780750340106, 978-0750340106
      ISBN10: 075034010X

      Description

      Book Synopsis

      This book is designed to consider the recent advancements in hospitals to diagnose various diseases accurately using AI-supported detection procedures. This work examines recent AI-supported disease detection techniques from prominent researchers and clinicians working in the medical imaging processing domain. Within this book, the integration of various AI methods, such as soft computing, machine learning, deep learning, and other related works will be presented. Real clinical images utilizing AI are incorporated. The book also includes several chapters on machine learning, convoluted neural networks, segmentation, and deep learning-assisted two-class and multi-class classification.


      Key Features:


      • Implementation of machine-learning-assisted disease detection


      • Implementation of CNN (Convolutional Neural Networks) based medical image segmentation and assessment


      • Implementation of deep-learning-based medical data assessment


      • Hybridizing machine learning and deep learning features to enhance detection accuracy


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